899 results about "Parameter control" patented technology

The invention relates to the technical field of abalone peptide production, and discloses an abalone peptide production process optimization and intelligent decision-making method and system, and the method comprises the steps: collecting production data through a multi-source sensor, and extracting features through a convolutional neural network; the genetic algorithm optimization model is combined with an adaptive mechanism and a multi-target fitness function to generate a process parameter optimization scheme; and the multi-objective production optimization model outputs optimal production process parameters by means of an improved particle swarm algorithm. In the hierarchical intelligent decision-making model, the planning layer realizes global resource allocation, the scheduling layer adjusts a process in real time based on a Bayesian network and the like, and the operation layer controls equipment through fuzzy logic and constructs quality closed-loop control. According to the method, the problems that parameter control depends on experience, data processing is difficult, optimization is one-sided, decision making is not intelligent and the like in traditional production are solved, data can be accurately processed, the process is optimized, decision making is intelligent, production efficiency, the raw material utilization rate and product quality are effectively improved, cost is reduced, and the application prospect is wide.

The invention relates to the technical field of power generation equipment control, and discloses an intelligent control method and system for a hydroelectric generating set speed regulator, and the method comprises the steps: employing an introduction variable structure and variable parameter control technology, and dynamically adjusting the control parameters of a power closed loop and an opening closed loop; real-time calculation and feedback control are carried out, and a speed regulator responds to a power grid frequency modulation Operating data of key parts of the speed regulator are collected in real time through a sensor, feature extraction and mode recognition are conducted on the data in combination with an artificial intelligence algorithm, and the operating state and potential faults of the speed regulator are recognized; constructing a fault tree model based on the speed regulator state monitoring parameters, carrying out hierarchical analysis on the speed regulator, and positioning the specific position and reason of the fault; and verifying and optimizing the fault diagnosis result, and generating a targeted fault processing suggestion. The system comprises a dynamic adjustment module, a state evaluation module and a fault analysis module. According to the invention, the operation efficiency and safety of the hydroelectric generating set speed regulator in a complex power grid environment are obviously improved.

The invention discloses a process parameter optimization control method and system for an automobile injection molding part, and belongs to the technical field of data processing, and the method comprises the steps: collecting sample data to train a feedforward neural network based on the historical processing record of a target injection molding part, and constructing a product quality prediction plug-in; performing parameter fluctuation influence analysis according to the historical processing record, and constructing a fluctuation influence analyzer; determining product demand characteristics of the target injection molded part in combination with the automobile use scene; and by taking the product demand characteristics as expectations, optimizing the process parameters by using the product quality prediction plug-in and the fluctuation influence analyzer, and outputting the optimal process parameters for processing control. The problems of large product quality fluctuation and low production efficiency caused by insufficient injection molding process parameter control precision in the prior art are solved. By combining historical records, product quality prediction plug-ins and fluctuation analysis, precise optimization of process parameters is realized, the product quality is stabilized, and the controllability and efficiency of the production process are improved.

The invention discloses a remote intelligent beer fermentation monitoring platform based on the Internet of Things, and relates to the technical field of fermentation control, a fermentation sample collection module is arranged to collect fermentation characteristic data and progress label data of a fermented beer sample in a fermentation test environment, and a progress model training module is arranged to train a progress prediction model; a progress judgment module is arranged to obtain the expected progress after the p moment output by the progress prediction model, and collect the actual fermentation progress after the p moment, and a fermentation regulation and control module constructs the state space, the action space and the reward function of a fermentation parameter decision model, and judges whether parameter regulation and control need to be performed based on the expected progress and the actual fermentation progress. If the parameters need to be regulated and controlled, generating an action decision of a subsequent fermentation process for the to-be-monitored fermentation tank through a fermentation parameter decision model; the automation and intelligence of the fermentation process are realized, the stability of the beer quality is improved, and the labor cost is reduced.

The invention provides a parameter control method and system in the friction stir welding process, and relates to the technical field of welding equipment of metal materials. The method comprises the steps that before friction stir welding is started, working condition information of a to-be-welded workpiece is input into a welding process simulation model for virtual test welding; screening out a plurality of groups of standard process parameter combinations meeting preset welding quality requirements; in the friction stir welding process, the change trend of all the technological parameters is determined according to the real-time technological parameter combination within the first preset time period; and if it is determined that the deviation risk exists in the current welding state within the second preset time period in the future according to the change trend, the standard technological parameter combination with the maximum similarity with the real-time technological parameter combination in the standard technological parameter library is determined as the target technological parameter combination to conduct parameter control adjustment on the welding equipment. By implementing the method, the welding defects caused by sudden change of the process window can be overcome, and the stability of the welding process and the consistency of the welding seam quality are improved.

The invention relates to the technical field of marking control, and discloses a control method and system for product marking. The method comprises the steps of scanning the surface of a part to obtain material data; performing three-dimensional positioning according to the material data to obtain coordinate data; marking parameters are screened according to the coordinate data; using the parameters to control the marking device to generate process data; analyzing the process data to evaluate the marking quality; and optimizing parameters by using the quality data and storing the parameters in a database to form a control scheme. According to the invention, accurate identification of the material and shape characteristics of the part can be realized, the optimal marking position and process parameters are automatically determined according to the identification result, real-time monitoring and adjustment are carried out in the marking process, the marking quality is comprehensively evaluated and fed back and optimized after the real-time monitoring and adjustment are completed, and the consistency and reliability of the marking quality are improved.

The invention provides an intelligent comprehensive system and method for steel production process parameter optimization, and the system comprises a data configuration module which is used for collecting quality-related data in a steel production process; the influence factor analysis module is used for processing data related to quality by using a feature engineering technology and identifying key variables; the quality index prediction module is used for constructing a quality prediction model by using a machine learning algorithm and key variables; the process parameter optimization module is used for constructing a process parameter optimization model based on the prediction result and the quality index control target, and analyzing and recommending an optimal process parameter control range by utilizing an intelligent algorithm; and the model monitoring optimization module is used for evaluating and optimizing the operation effects of the quality prediction model and the process parameter optimization model in real time. According to the method, the whole-process intelligent management from data configuration and key factor identification to quality prediction, process parameter optimization and model dynamic monitoring is realized, a closed-loop optimization mechanism is formed, and the production efficiency and the product quality are effectively improved.

The invention discloses a galvanized steel pipe coating process control method and system, and the method comprises the steps: obtaining galvanized layer integrity prediction information based on obtained galvanizing process selection information and a preset galvanized layer integrity prediction model; based on the obtained welding process control parameters and a preset welding quality prediction model, welding quality prediction information is obtained; analyzing in combination with the zinc coating integrity prediction information and the welding quality prediction information, judging whether the prediction information meets a preset process control index or not, and obtaining parameter model input information according to a judgment result; inputting the parameter model input information into a preset fusion process control model to obtain parameter control information and coating reference control information; on the basis of the parameter control information and the coating reference control information, the galvanizing welding process and the coating process of the galvanized steel pipe are controlled; the galvanized steel pipe coating technology is more reliable and efficient, and the quality and performance of the galvanized steel pipe are improved.

The invention relates to the technical field of fastener process production, in particular to a process parameter control method and system applied to fastener production. The method comprises the following steps: acquiring three-dimensional cutting force of a tool-workpiece contact area in a fastener thread machining process in real time, and generating cutting force dynamic fluctuation characteristic data; the real-time abnormal situation of the current machining process is recognized according to the cutting force dynamic fluctuation characteristic data, a tool wear mode is judged, thread ring machining deviation prediction is conducted, and a predicted thread geometric deviation value is generated; and adjusting multiple machining control parameter values according to the predicted thread geometric deviation value, and carrying out real-time machining feedback monitoring so as to realize fastener production self-adaptive control. According to the method, intelligent recognition of the tool wear mode and accurate prediction of the machining deviation are achieved through cutting force sensing, and it is ensured that the thread machining precision of the fastener is stable and controllable through multi-parameter cooperative self-adaptive regulation and control.

The invention relates to the technical field of plastic processing, and discloses an environment-friendly plastic product extrusion molding intelligent parameter control system and method, and the system comprises a data collection and fusion module, a causal association construction module, a digital twinning and virtual-real interaction verification module, an intelligent control module, a self-adaptive reconstruction module, and a man-machine interaction and visualization module. The method comprises the steps of collecting data in real time, and performing deep fusion to generate features; dynamically constructing a knowledge graph by fusing features, and synchronously updating causal topology; constructing a digital twinborn model, and performing virtual operation prediction; generating an instruction to regulate and control the microstructure; recognizing and classifying disturbances, and reconstructing a causal topology to guide strategy adjustment; the system state is displayed in real time, and operation intervention is supported. On-line microstructure data are acquired and deeply fused in real time through the data acquisition and fusion module, and a deep correlation model is constructed in combination with the microstructure guide reverse deduction unit, so that the problems of large batch difference and unstable physical properties of environment-friendly plastic materials are effectively solved.

The invention relates to the technical field of printed circuit board manufacturing, in particular to a PCB lamination parameter control method and system, and the method comprises the steps: receiving a global pressure adjustment instruction; acquiring real-time temperature data of the to-be-laminated sheet, and constructing a surface temperature distribution diagram of the to-be-laminated sheet; the surface temperature distribution diagram is analyzed, and operation areas, with different thermal response attributes, of the to-be-laminated sheet are divided; according to the thermal response attribute of each operation region and the global pressure adjustment instruction, obtaining a region area weight and a response deviation coefficient, carrying out differential decomposition on the global pressure adjustment instruction, and calculating differential pressure adjustment amounts of the plurality of operation regions; and mapping the differential pressure adjustment amount to a multi-partition hydraulic execution mechanism in the laminating equipment, and controlling a target pressure value output by each operation area. The method has the advantages that refined and differentiated pressure adjustment of operation areas with different thermal response attributes in the plate can be achieved, and local defects caused by uneven material response are effectively avoided.

The invention relates to the technical field of tool control, in particular to a tooth cutting tool parameter control system based on bevel angle cutting, which comprises a tool parameter acquisition module used for acquiring the rotating speed, the axial feeding amount and the cutting depth of a tool in real time; the force-heat prediction model is used for outputting predicted cutting force and predicted cutting tool temperature; the multi-target parameter optimization model is used for receiving constraint conditions set by a user, optimizing the rotating speed, the axial feeding amount and the cutting depth of the cutter by taking the lowest cutting force, the lowest temperature of the cutting cutter and the highest machining efficiency as targets in the constraint conditions, and integrating and outputting a regulation and control strategy; and the cutter parameter control module is used for regulating and controlling the rotating speed, the axial feeding amount and the cutting depth of the cutter based on a regulation and control strategy when the predicted cutting force and the predicted temperature of the cutting cutter exceed threshold values. According to the method, by accurately regulating and controlling the parameters of the tooth cutting tool, the machining efficiency of the tooth cutting tool can be ensured, and meanwhile the abrasion speed of the tooth cutting tool is reduced.

The invention discloses an intelligent tension control datamation method and system, and relates to the technical field of tension control. An intelligent tension control datamation system comprises a target equipment tension acquisition module, a target equipment tension prediction module and a target equipment tension adjustment module. The real-time tension information and the parameter information of the target equipment are acquired at preset time intervals, so that the state of the equipment is monitored and analyzed in real time; the tension data in the next preset time interval can be predicted by using the target equipment tension prediction model, so that the potential tension deviation problem can be found in advance; by comparing the to-be-analyzed tension data with the predicted tension data, whether the target equipment needs to be adjusted or not can be actively judged, instead of passively responding only after the tension exceeds a preset range; and the target equipment parameter control model can output an optimal parameter control scheme according to the prediction information and the current parameter information, and the equipment performance is optimized.

The invention relates to the technical field of spraying control, and discloses a water turbine spraying process parameter real-time monitoring, regulating and controlling method and system.The water turbine spraying process parameter real-time monitoring, regulating and controlling method comprises the following steps that multi-modal data in the spraying process is collected, and a four-dimensional data structure is constructed; tensor decomposition is carried out, and a core feature tensor and a factor matrix are extracted; constructing an enhanced game strategy model, and outputting a process parameter control strategy; lyapunov optimization is introduced, and regulation and control input is generated; the control strategy and the control input are combined to generate a spraying execution action; and performing feedforward compensation based on the disturbance observer to form a final control instruction. According to the method, the multi-modal process data fusion and tensor decomposition technology is adopted, the four-dimensional data tensor is constructed, the core features of the spraying process are extracted, and by means of the method, the system can more comprehensively capture dynamic changes in the spraying process, and an accurate technological parameter control strategy is provided.

The invention discloses a thermal power plant boiler combustion optimization method and system, and the method comprises the steps: obtaining historical combustion data and historical control data of a thermal power plant boiler, and carrying out the analysis to determine control parameters affecting the combustion; extracting features of the control parameters, and constructing a combustion data prediction model based on the features and a preset neural network model for prediction to obtain combustion prediction data; analyzing the combustion prediction data, determining combustion data characteristics, and determining a combustion state coefficient of the thermal power plant boiler based on the combustion data characteristics; an expected combustion state coefficient preset in advance by the thermal power plant boiler is obtained, and the difference value between the combustion state coefficient and the expected combustion state coefficient is determined; and determining a parameter control optimization coefficient according to the difference value to optimize the current control parameter. According to the invention, refined and intelligent monitoring and optimal control of the combustion process can be realized, so that the combustion efficiency of the thermal power plant boiler is improved, the cost is reduced, the emission is reduced, and the stability and the safety of boiler operation are improved.

The invention discloses an operation system and method of a full-automatic coating machine, and relates to the technical field of coating processing control, and the system comprises a data acquisition module which obtains various preset parameters when a current coating machine performs coating operation on a current base material, obtains defect data which easily occurs when the current coating machine performs coating operation on the current base material based on a preset database, and transmits the defect data to a database processing module; the defect data comprises defect positions and defect types; according to the method, a complete parameter regulation and control system is formed through close combination of a risk assessment function and a grading early warning mechanism with technologies of dynamic association judgment, parameter linkage adjustment and the like, and before parameter adjustment, whether linkage adjustment is needed or not is determined through dynamic association judgment; in the adjusting process, the risk is evaluated through a risk evaluation function, and a corresponding adjusting strategy is executed according to the risk level.

The invention provides a cast-in-place pile construction system and method in a soft foundation area. The system comprises a drilling system, a grouting system, a monitoring system and a control system, wherein the drilling system is used for drilling and monitoring and optimizing the drilling condition; the grouting system is used for grouting into the drill hole and optimizing grouting parameters; the monitoring system is used for monitoring conditions in the drill hole and slurry parameters of grouting; the control system is electrically connected with the drilling system, the grouting system and the monitoring system and used for controlling the drilling system to drill holes and the grouting system to grout and adjusting construction parameters of the drilling system and the grouting system according to information monitored by the monitoring system. According to the invention, the drilling system and the grouting system can perform monitoring and optimization, and meanwhile, the monitoring system performs real-time monitoring, so that the control device can conveniently adjust the drilling system and the grouting system, the construction quality of the cast-in-place pile is improved, the construction efficiency can be improved, and even if a problem encounters in the construction process, the problem can be timely monitored and optimized.

The invention discloses an annealing furnace temperature parameter control method and system based on multi-source data, and relates to the technical field of annealing furnace temperature parameter control, and the method comprises the following steps: carrying out the data collection of the operation process of an annealing furnace, and generating an annealing process record; a temperature sensor is arranged in an annealing furnace to collect the temperature in the furnace in real time, the uniformity of a temperature field in the furnace is measured by calculating a temperature equilibrium coefficient, and time parameters used for compensating the heat conduction hysteresis effect are determined according to material characteristics and thickness parameters of a workpiece to be processed; based on the temperature equilibrium state monitored in real time and process requirements, the annealing process is subjected to control stage division; a comprehensive uniformity index is calculated by analyzing the temperature balance degree and the cooling rate uniformity at all moments in the annealing process, whether the control stage of the annealing furnace is abnormal or not is judged according to the condition that the fluctuation amplitude of the index at all moments does not exceed the preset multiple of the average value of historical uniformity indexes of workpieces of the same type, and temperature parameter control over the annealing furnace is achieved.

The invention relates to the technical field of cloth bag processing, and discloses a non-woven fabric bag processing parameter regulation and control method and system based on deep learning, and the method comprises the steps: obtaining the real-time rotation speed and tension data of equipment, carrying out the signal filtering and state calculation, obtaining a cloth traction state, carrying out the fuzzy logic processing, and determining the adjustment amount; obtaining a target rotation speed adjustment amount; according to the target rotation speed adjustment amount, threshold judgment and parameter dynamic updating are carried out, a new tension fluctuation index is obtained, fitness evaluation is carried out, and the product specification fitness is obtained; according to the product specification fitness, a dynamic adjustment decision is made, a parameter regulation and control scheme is obtained, risk quantification is carried out, and a production interruption risk level is obtained; and according to the production interruption risk level, risk threshold verification and optimization algorithm correction are carried out, a defective percentage inhibition value is obtained, tension stable signal analysis and global fusion output are carried out, and final processing equipment parameter configuration is obtained. The method can improve the qualified rate of products.

The invention discloses a control method of a hybrid energy storage system and the hybrid energy storage system, and relates to the technical field of hybrid energy storage systems.The control method comprises the steps that corresponding simulation control parameters of the hybrid energy storage system under different operation conditions are obtained, and the simulation control parameters are parameters used for simulating the characteristics of a battery cluster; and controlling the operation state of each energy storage converter according to the simulation control parameters. By adopting the method, the flywheel can be controlled to simulate the characteristics of the battery to work, the cost of the hybrid energy storage system can be effectively reduced, and the complexity of the control process of the hybrid energy storage system is reduced.

The invention discloses a control method and device of cooking equipment and the cooking equipment. The cooking equipment comprises an air frying module and a microwave module. The control method of the cooking equipment comprises the following steps: acquiring characteristic parameters of food materials; determining operation parameters of the cooking equipment according to the characteristic parameters of the food materials and a preset mapping relation table; wherein the preset mapping relation table is a corresponding relation table of the characteristic parameters of the food materials and the preset operation parameters of the cooking equipment; controlling the air frying module or the microwave module to work according to the operation parameters so as to improve the cooking speed of the food materials. According to the control method of the cooking equipment, the operation parameters of the cooking equipment can be determined according to the characteristic parameters of the food materials and the preset mapping relation table, and the air frying module or the microwave module in the cooking equipment is controlled to work according to the operation parameters; the dehydration speed of food formed by processing the food materials is increased, the cooking process is accelerated, the cooking time is shortened, and the cooking effect of crispy outside and tender inside is achieved.

The invention relates to the technical field of vacuum coating, and particularly discloses a control system for a vacuum coating machine, which comprises a vacuum stable state analysis module, a gas flow matching analysis module, a coating environment control analysis module and a coating parameter control analysis module. Pressure intensity values of monitoring time points in all control time periods are accurately collected through a capacitive pressure sensor, the average value of the pressure intensity is calculated, the overall level of the vacuum pressure intensity in the time period can be visually reflected, and basic data are provided for judging whether the vacuum degree is in a proper range or not; an active monitoring and prevention mechanism is adopted for the vacuum coating machine, so that the continuity and the stability of coating production are guaranteed, a scientific basis is provided for preventive maintenance of the equipment, the service life of the equipment is prolonged, the probability of sudden failure of the equipment is reduced, the reliability, the high efficiency and the intelligent level of the whole vacuum coating production system are improved, and the production cost is reduced. And the competitiveness of enterprises in the field of coating processing is improved, the production cost is reduced, and the product quality is improved.

The invention relates to the technical field of precision casting, and discloses a high-precision control method for stainless steel castings, which comprises the following steps: preparing raw materials, recording component characteristics of the raw materials, designing a formula proportion of the raw materials, carrying out pouring process design, and setting a parameter control system in each link of pouring, according to the shape of the needed stainless steel casting, mold design and manufacturing and mold quality control are carried out, grinding tool design parameters are recorded, a stainless steel casting solidification process simulation model is established according to raw material component characteristics, a raw material formula proportion, a designed pouring process and the mold design parameters, and the casting solidification process is simulated in the model. The method comprises the following steps: predicting a defect area in a casting production process, carrying out advanced prevention and optimization treatment on the defect area according to the predicted defect area in the casting production process, strengthening a refining degassing operation in a casting process, further carrying out a metal solution purification step after refining degassing, and demolding the casting, and the mold is cleaned, checked and maintained in time.

The invention provides a multi-parameter regulation and control method and system for a vacuum insulation panel heat insulation layer spraying robot, relates to the technical field of multi-parameter regulation and control, and effectively solves the problems of uneven spraying thickness and poor space consistency by dynamically sensing and regulating and controlling the interference relation and track offset influence among multiple nozzles in the spraying process. Fine adjustment of parameters of the spray heads can be achieved, all the spray heads can maintain the ideal spraying state under different working conditions, and therefore the overall spraying precision and stability are improved. By introducing a multi-parameter combined regulation and control mechanism, spraying defects caused by factors such as attitude deviation and coupling interference can be remarkably reduced, and the rework rate and material waste are reduced.

The invention belongs to the field of production quality traceability, and particularly relates to an abnormity traceability and parameter regulation and control system for a premix production line, which comprises a monitoring module, a reverse mapping module and a forward adjustment module, a monitoring module can acquire whole-course fingerprint information of an abnormal production process in real time by constructing a whole-course tracking chain containing a process-control association relationship; the reverse mapping module performs reverse whole-course reasoning by using a hidden Markov algorithm, performs longitudinal local reasoning in combination with an index mapping relation, accurately locates an abnormal source, and generates a reverse abnormal information fingerprint chain; and the forward adjustment module performs forward processing control parameter adaptive adjustment from the abnormal starting node according to the fingerprint chain and a preset correction strategy until all indexes return to normal. According to the invention, closed-loop intelligent control from abnormity monitoring and source tracing to production self-adjustment is realized, and the quality consistency and tracing efficiency of premix production are remarkably improved.

The invention relates to a method and device for designing a controller of a direct-current converter and a medium, and the method comprises the following steps: determining a control condition of the direct-current converter according to a controller design scene, and inputting the control condition into a large language model; establishing a mathematical model of the direct-current converter according to control conditions by using a large language model, and calculating converter control parameters; designing and verifying a circuit simulation model according to the converter control parameters; outputting a controller parameter control code by using a large language model according to the circuit simulation model; and running a controller parameter control code, an inspection program and a controller performance index, and iteratively eliminating error information to obtain a coding result. Compared with the prior art, the method has the advantages of short waiting time and high accuracy.

The invention discloses a control method and device for a loading and unloading clamp based on pneumatic and electromagnetic composite self-locking, and relates to the technical field of logistics automation equipment. The method comprises the steps that size information and material information of goods to be loaded and unloaded are acquired; acquiring initial position information and target position information of goods to be loaded and unloaded; based on the size information, the material information, the initial position information and the target position information, clamping parameters of the loading and unloading clamp are determined, and the clamping parameters are clamping jaw control parameters of the loading and unloading clamp; and controlling the loading and unloading clamp to clamp the to-be-loaded and unloaded goods based on the clamping parameters of the loading and unloading clamp. The technical problem that in the prior art, automatic loading and unloading equipment is poor in adaptability is solved.

The invention provides an evaporation energy-saving self-adaptive regulation and control method and system under multi-parameter analysis, and relates to the technical field of data processing, and the method comprises the steps: obtaining an evaporation control parameter space of a single-effect evaporator, and randomly selecting a plurality of initial evaporation control parameters meeting a uniform distribution constraint; based on the solution attributes, the environmental parameters and the expected concentration indexes of the to-be-evaporated saline water, evaporation efficiency prediction of the multiple initial evaporation control parameters under multiple nodes of a preset time zone is executed, multiple predicted evaporation efficiency sets are obtained, and multiple evaporation fitness degrees are obtained through evaluation; and by taking the evaporation control parameter space as a constraint, carrying out evaporation control parameter optimization according to the plurality of evaporation fitness, outputting an optimal evaporation control parameter, and controlling the single-effect evaporator to carry out evaporation operation. The technical problems that in the prior art, due to the fact that a multi-parameter collaborative optimization method is lacked, energy consumption is high in the brine evaporation process, and adaptability to environment changes is poor are solved, and the technical effects of improving evaporation efficiency and reducing evaporation energy consumption are achieved.

The invention relates to the technical field of intelligent decision making, and discloses an intelligent decision making method and system based on a computing network integrated industrial PLC, and the method comprises the steps: carrying out the time slice distribution of control parameters of water supply equipment, and dividing the decision period of the PLC, and obtaining an initial control parameter queue; determining occurrence probability distribution of a normal operation state, an efficient control state and a decision conflict state to obtain a water supply parameter conflict probability table; redistributing the parameter control time resource to obtain a water supply parameter optimization control time sequence; converting the parameter groups which still have conflicts into mutually independent control variables, and respectively executing optimization calculation to obtain a multi-parameter parallel control instruction of the water supply equipment; and carrying out dynamic resource scheduling on the multi-parameter parallel control instruction of the water supply equipment to generate an energy-saving control scheme of the water supply equipment. The method effectively optimizes the dynamic distribution of control resources, remarkably shortens the response time of control parameters, and improves the overall throughput of the system.

The embodiment of the invention provides a washing machine, a control method and device of the washing machine and a storage medium, the control method of the washing machine comprises the steps that clothes information of clothes to be washed in the washing machine and temperature and humidity information in the washing machine are obtained, and the clothes information comprises materials, stain types and weight; predicting washing parameters according to the clothes information and the temperature and humidity information; and controlling the washing machine to operate based on the washing parameters. The washing parameters are predicted according to the clothes information and the temperature and humidity information, that is, the washing parameters can be dynamically adjusted, compared with existing fixed washing parameters, changes of the washing environment can be dynamically responded, the flexibility of the washing machine is improved, and then the energy utilization efficiency is improved.