1978 results about "Water chiller" patented technology

The invention relates to the technical field of air conditioner chilled water control, in particular to an air conditioner chilled water control method and system based on deep learning, and the method comprises the following steps: collecting states of an air conditioner water chilling unit, including water pump frequency and valve opening feedback, and pipe network water supply temperature, return water temperature, flow and differential pressure operation readings; according to the method, the state parameters of the water chilling unit are dynamically collected, the system operation state feature set is constructed, real-time fusion and standardization processing of multi-source heterogeneous data are achieved, the problem of time sequence dislocation caused by sensor sampling frequency differences is solved, the heat load change key input quantity is recognized based on the feature set, and the system operation state feature set is established. And the performance attenuation trend of the water pump is accurately pre-judged in combination with prediction calculation, and extra energy consumption caused by lagging adjustment is reduced. A layered optimization framework with total energy consumption minimization as a target is introduced, water supply temperature, pressure difference setting and unit operation combination are decoupled into independent optimization sub-problems, and invalid work of a water pump is reduced on the premise that the tail end heat requirement is met.

The invention discloses an integrated cold station intelligent control system based on multi-modal data fusion, and relates to the technical field of data fusion, an intelligent decision and optimization module adopts reinforcement learning and model prediction control based on fused data to realize dynamic optimization of start and stop of a water chilling unit, chilled water temperature setting and water pump frequency adjustment; the fault detection and adaptive optimization module evaluates the data fusion accuracy by calculating an environment entropy value and cold station dynamic response delay time, and dynamically adjusts a control strategy based on a prediction deviation rate and the data fusion accuracy; the closed-loop feedback module analyzes and adjusts control parameters through operation data, intelligent control models between different cold stations are optimized through transfer learning, intelligent deployment of a new cold station is accelerated, and the generalization ability of the models is improved. More accurate, more energy-saving and more stable intelligent control of the cold station is realized, and the operation efficiency and reliability of the cold station system are improved.

The invention discloses an energy-saving control method and system for a water chilling unit, and relates to the technical field of energy-saving control. During operation of the system, a data set is synchronously collected from a water chilling unit system through a multi-channel asynchronous sampling mechanism, time sequence compression and redundancy removal are carried out, an embedded perturbation calculation mechanism is used for calculating and generating a non-dominant control core coefficient, and the non-dominant control core coefficient is used for controlling the energy-saving control of the water chilling unit; a three-dimensional coefficient space is converted and output through an entropy state change structure and is used for constructing a state balance atlas, comprehensively calculating a control state index SEEI, evaluating the current energy state offset degree of a system, determining whether intervention is carried out or not, carrying out rule search and nonlinear modeling based on the control state index SEEI value, generating an adjustment matrix, and carrying out state balance analysis. And starting a data reconstruction micro-strategy of a short-time historical window, receiving an adjustment matrix, converting the adjustment matrix into a device-level instruction, executing an action through an edge controller, feeding back a response error epsilon (t) in real time, and predicting a potential performance degradation trend based on long-time system operation data.

Vehicle heat pump system comprising a compressor for discharging a refrigerant; an indoor heat exchanger in an air-conditioning case, allowing heat exchange between air and the refrigerant; a water-cooled condenser downstream of the indoor heat exchanger in the flow direction of the refrigerant, exchanging heat with first cooling water; an outdoor heat exchanger downstream of the water-cooled condenser, allowing heat exchange between the refrigerant and outdoor air; an evaporator in the air-conditioning case, allowing heat exchange between the refrigerant and the air to cool the indoor space, and a chiller downstream of the outdoor heat exchanger exchanging heat with second cooling water. An outdoor unit bypass line allowing refrigerant to pass through the water-cooled condenser and bypass the outdoor heat exchanger, which branches off between the water-cooled condenser and the outdoor heat exchanger and is connected to the upstream side of the chiller in the flow direction of the refrigerant.

The invention discloses an intelligent air conditioner water chilling unit control method and system based on predictive optimization. Operation data and weather forecast data are collected to establish a dynamic response reference, building cold load sudden change opportunity is recognized, the mismatching relation between magnetic suspension frequency and wet bulb temperature is detected, and energy-saving opportunity recognition data is generated to determine a cooling starting judgment table; identifying equipment response delay characteristics by using a dynamic response reference, extracting time sequence advantage parameters to determine dislocation configuration among multiple pieces of equipment, and generating coordination control parameters; cloud-local transmission delay analysis is carried out according to the coordination control parameters, and a coordination control sequence is generated through buffer opportunity identification and delay compensation; mechanical refrigeration suppression data is generated through energy efficiency mode classification, free cooling potential mining is implemented to form a cold source optimization factor, and an emergency response strategy is generated; an emergency response strategy is used to identify a multi-device linkage trigger critical zone, a prediction correction feedback network is constructed, a global collaborative optimization instruction is generated, and the system operation efficiency and the control precision are improved.

The invention provides a magnetic suspension centrifugal water chilling unit, and belongs to the field of refrigeration equipment. The magnetic suspension centrifugal water chilling unit comprises a magnetic suspension compressor, a condenser and an evaporator, the magnetic suspension compressor is connected with the condenser through an exhaust pipeline, and the condenser is connected with the magnetic suspension compressor and the evaporator through a liquid supply pipeline assembly; the system further comprises a natural process control module, the natural process control module is used for dynamically adjusting the starting sequence of a plurality of magnetic suspension compressors in the water chilling unit by determining the energy efficiency health index of the water chilling unit and calculating the energy efficiency health index, and the natural process control module is electrically connected with the central controller. And a natural process control module is arranged, a multi-dimensional energy efficiency health index model is constructed, and the starting sequence of the compressors is dynamically adjusted by integrating the actual energy efficiency ratio, the evaporation efficiency, the compressor aging coefficient, the pressure fluctuation and the environment humidity correction term.

A heat pump system for a vehicle includes: a valve, an electrical component cooling device, a battery cooling device, an indoor heating device, an indoor cooling device, a centralized energy device, and a chiller, wherein the second line is selectively fluidically-connectable to the first line connected to the radiator through the second valve; a condenser included in the centralized energy device is selectively fluidically-connectable to the first line or the second line through a third valve to condense the refrigerant supplied through the refrigerant line through heat-exchange with a coolant provided in a sixth line through which a coolant flows; and a first end portion of the third line is selectively fluidically-connectable to the sixth line through a fourth valve provided in the sixth line.

The invention discloses an air conditioner supply and demand collaborative optimization scheduling method, which relates to the technical field of air conditioner supply and demand scheduling, and comprises a sensing prediction module, an acquisition comparison module, a deviation correction driving module, a control adjustment module, a cold source control module, a strategy adjustment module and an anomaly detection module. When the abnormality detection module detects that the air conditioner terminal breaks down, the control adjusting module enhances the power of the peripheral equipment to fill the cooling capacity gap, if the water chilling unit breaks down, the cold source control module starts the standby unit to switch the cooling capacity output path, and when the cooling capacity is insufficient, the control adjusting module is in linkage to reduce the air volume of the low-priority area to preferentially guarantee cooling of the core area; meanwhile, a strategy adjusting module automatically matches a predefined strategy chain according to the fault type, for example, global average temperature control is switched when temperature control fails, a load balancing strategy is triggered to be distributed to a standby unit when equipment is overloaded, and the strategy is gradually rolled back to the optimal strategy based on historical data after the fault is repaired; and strategy conflicts and equipment fluctuations are avoided through progressive improvement of cold energy supply.

The invention discloses a water-cooling central air conditioner load management and control method based on artificial intelligence, and relates to the technical field of load management and control. Load prediction is carried out by combining a long and short-term memory time sequence model and a physical constraint neural network in a water chilling unit load prediction link and utilizing historical data; errors are corrected through an energy balance equation of the water chilling unit, and the prediction accuracy is improved; multi-objective optimization control is adopted, COP maximization of a water chilling unit, energy consumption minimization of a cooling tower fan and cooling water supply temperature stability serve as optimization objectives, environment temperature and humidity prediction is combined, and a cooling water supply temperature set point and a cooling tower fan start-stop strategy are dynamically calculated; based on a cooling water supply temperature set point and a fan start-stop strategy, a water chilling unit, a cooling tower fan and a water pump are dynamically adjusted, and the high-frequency operation phenomenon is reduced through fan start-stop optimization.

The invention provides a high-efficiency control method and system for a central air conditioner refrigeration machine room, and relates to the technical field of automatic control, and the method comprises the steps: 1, obtaining chilled water supply and return water temperature difference and flow data, and calculating the dynamic cold load demand of a building in combination with the personnel distribution thermal imaging data of each floor; and 2, on the basis of the dynamic cooling load requirement, a dynamic adjustment model for the number of running water chilling units is built, matching degree calculation is conducted on the actual cooling load value and the single refrigerating capacity of the water chilling units through a fuzzy PID control algorithm, and a final unit running combination scheme is generated. By calculating the cooling load requirement, dynamically adjusting the operation parameters of the water chilling unit, the chilled water pump and the cooling tower and balancing the equipment operation time, the system energy efficiency is effectively improved, the energy consumption and the operation and maintenance cost are reduced, and stable operation of the refrigerating system is guaranteed.

The invention provides an ultra-pulse thulium fiber laser therapy apparatus which comprises a laser, an electrical device and a coupler, the laser is connected with the coupler through a thulium fiber, the laser and the coupler are respectively connected with the electrical device through circuits, and the electrical device is connected with the coupler through a thulium fiber. The electrical device controls the operation of the laser and the coupler, the optical fiber is a thulium optical fiber emitted by the laser, and the wavelength of the laser is 1940 nanometers. The ultra-pulse thulium fiber laser therapy apparatus replaces a previous water cooling device and adopts a 1940nm laser internal air cooling device, so that the ultra-pulse thulium fiber laser therapy apparatus is more compact in structure, lighter in weight and smaller in size, and the problems of noise, frequent maintenance and replacement and the like caused by a large cooling-water machine are solved.

The invention relates to the technical field of non-electrical variable control, and discloses an industrial water chiller temperature intelligent adjusting system, which comprises a refrigeration circulation loop and a control unit, the control unit calculates a steady state control component based on the water outlet temperature deviation, performs differential processing on the refrigerant pressure to extract the gradient, and outputs the gradient. Generating a transient compensation component when the gradient exceeds a dynamic noise threshold; according to the method, the problem of thermal lag is solved by utilizing the pressure wave transmission speed advantage, aggressive response is prevented from triggering low-pressure shutdown through a safety margin constraint mechanism, the pressure safety margin is calculated in real time, a gain coefficient is determined according to a nonlinear model, and a final driving instruction is generated. And the dynamic balance of the control response speed and the system physical security boundary is realized.

The invention relates to the field of factory intelligent cooling, and discloses an MPC-based large factory intelligent cooling system and a cooling control method, the system comprises a data acquisition module, an AI control module, a cooling tower control module, a cooling water pump control module and a cooling-water machine control module; the data acquisition module acquires outdoor environment temperature and humidity, cooling tower outlet water temperature, cooling water pump inlet and outlet water temperature difference and flow and water chiller operation state data in real time. The AI control module constructs a system model through real-time data, predicts and optimizes by using an MPC algorithm, and calculates optimal values of the running frequency of a cooling tower fan, the running frequency of a cooling water pump and the power of a cooling-water machine compressor by adopting sequential quadratic programming, so as to realize cooperative dynamic control of equipment in the system; the overall operation efficiency of the cooling system under the outdoor temperature and humidity change condition is effectively improved, and the overall energy consumption of the system is minimized in real time.

The invention relates to the technical field of intelligent control, in particular to an inspection system and method for a heating and ventilation system based on a knowledge graph, and the system comprises a feature extraction module, a graph construction module, an anomaly tracing module, a causal analysis module and a priority module. According to the method, the inlet and outlet water temperature and flow data of the water chilling unit are collected, deviation characteristics are extracted in combination with principal component analysis, the operation state is quantified, an embedded map participates in state judgment, the anomaly detection capacity is improved, initial anomaly and upstream nodes are focused, the analysis range is narrowed, and causal tracing is carried out based on the state influence between devices; by means of a Bayesian network, a state evolution chain is constructed, a time sequence and an inter-structure fault are bridged, task priority is evaluated according to a link starting point and length, equipment dynamic sorting and state updating are carried out, inspection scheduling accuracy and efficiency are improved, and a closed-loop process which is high in recognition accuracy, small in analysis boundary, clear in path and excellent in resource allocation is formed.

The invention provides a system-level collaborative water-cooling energy-saving control device and method based on AI fusion refrigeration, and the device comprises an edge calculation unit which is used for receiving the operation working condition parameters, the output working condition and refrigerating capacity prediction information of a refrigeration system, and a water-cooling system control strategy; the cooperative control unit is used for receiving the control strategy pushed by the edge computing unit and performing cooperative control on each device of the water cooling system; the collecting unit is used for collecting operation parameters of the refrigerating system. By establishing the complete system energy consumption model and the multi-constraint optimization algorithm, global optimization control over equipment such as a water chilling unit, a water pump and a cooling tower is achieved.

The invention relates to the technical field of unit detection, and discloses an intelligent fault self-diagnosis method for an evaporative condensation integrated screw water chilling unit, which comprises the following steps of: decoupling operation data of a compressor through a blind source separation algorithm, performing image processing on operation data of a condenser in combination with a morphological analysis method, and performing fault diagnosis on the operation data of the condenser; the operation characteristics of the compressor and the operation characteristics of the condenser can be extracted respectively, effective decoupling and clear expression of coupling signals are realized, and by constructing a dual-channel LSTM network comprising a gating fusion unit and introducing a cross-channel coupling gating mechanism, the system reliability is improved. The dynamic coupling relation between the compressor and the condenser can be modeled and regulated in the time dimension, the coupling mechanism between the compressor and the condenser is truly reflected, the time sequence parameter sequence is input into the pre-trained deep LSTM network, the fault types such as control lag and performance degradation can be accurately recognized, and the fault diagnosis accuracy is improved. Therefore, the accuracy and real-time performance of fault diagnosis are improved, and the requirement for intelligent fault management of the water chilling unit is met.

The invention discloses an energy-saving type magnetic suspension centrifugal water chilling unit, and relates to the technical field of refrigeration, the energy-saving type magnetic suspension centrifugal water chilling unit comprises a magnetic suspension compressor, a variable-diameter throttling mechanism and a heat exchange system, the heat exchange system is fixedly installed on the side face of the outer wall of the magnetic suspension compressor, and the variable-diameter throttling mechanism is fixedly installed on the side face of the outer wall of the heat exchange system; an outlet of the magnetic suspension compressor is directly connected with the heat exchange system through a pipeline, and the reducing throttling mechanism is connected with the heat exchange system through a pipeline. The front-stage closed impeller and the rear-stage semi-open impeller are coaxially connected in series, efficient compression without mechanical contact and oil lubrication is achieved, the problems that a centrifugal compressor is high in energy consumption and large in vibration due to mechanical friction are solved, and the energy efficiency ratio of a unit is effectively increased.

The invention provides a water chiller predictive maintenance method and system based on digital twinning, and the method comprises the steps: obtaining the evaporation pressure, suction temperature, refrigerant flow and outlet water temperature parameters during the operation of a main module of a water chiller, and carrying out the synchronous collection through multiple sensors, thereby forming a time series data set; according to the time sequence data set, a sliding window method is adopted to extract the mean shift amount, variance volatility and cross correlation coefficient of evaporation pressure and suction temperature, and a collaborative drift mode reflecting micro leakage is obtained; according to the corrected drift rate and cross correlation coefficient, generating a feature vector of a collaborative change direction among the evaporation pressure, the suction temperature and the refrigerant flow; and by calculating the Euclidean distance between the feature vector of the cooperative change direction and the health baseline, whether the micro leakage reaches the early warning triggering degree is judged, and the strength of an early warning signal is obtained.

The invention provides a water chilling unit performance prediction method based on an improved physical information neural network. The method comprises the following steps: step 10, constructing a neural network model; step 20, selecting to obtain a neuron variable, and embedding the neuron variable into the neural network model as a physical neuron to obtain a physical neuron embedded physical information neural network model; step 30, introducing a loss function into the physical neuron embedded physical information neural network model; 40, carrying out data balance processing on the original data set, and screening to obtain a training set; step 50, utilizing the training set to train the physical neuron embedded physical information neural network model to obtain a water chilling unit performance prediction model; and step 60, predicting the performance of the water chilling unit by using the water chilling unit performance prediction model. According to the improved water chilling unit performance prediction method based on the physical information neural network, high-precision prediction of the performance of the water chilling unit is achieved, and the generalization ability and the model interpretability are improved.

The utility model relates to the technical field of biodegradable materials, and discloses an extruder cooling device for production of biodegradable material products, which comprises an extrusion pipe, a circulating cooling part, a liquid inlet pipe, a liquid outlet pipe, a water tank, a circulating pump, a filling port and a cooling-water machine, the liquid inlet pipe flange is connected to one end of the circulating cooling piece, the liquid outlet pipe flange is connected to the other end of the circulating cooling piece, the water tank is arranged at the other end of the liquid outlet pipe, the circulating pump is fixedly connected to the top of the water tank, and the other end of the liquid inlet pipe is connected with a top flange of the circulating pump. According to the extruder cooling device for producing the biodegradable material products, the cooling pipes are uniformly distributed outside the extrusion pipe, so that cooling liquid is input into the cooling pipes through the water distribution pipes to ensure uniform cooling of the extrusion pipe, the cooling effects of all positions of the extrusion pipe are consistent, and the condition of non-uniform cooling is avoided.

The invention relates to a data center equipment type selection method based on electrical and heating ventilation load linkage, and belongs to the technical field of data center infrastructure design. The model selection method comprises the steps of setting basic data, obtaining the number of machine rooms and the number of IT devices in a single machine room, obtaining the total power of the IT devices, setting an energy efficiency index set value, obtaining the project power consumption scale, obtaining the total cooling load, selecting models of air conditioners at the tail ends of the machine rooms and substations, selecting models of water chilling units, selecting models of heat exchangers, selecting models of cooling water pumps and chilled water pumps and selecting models of cooling towers. And obtaining the total power of the air conditioner, obtaining an energy efficiency index accounting value, and carrying out PUE verification. According to the method, through closed-loop iteration of electrical load-heating and ventilation load-PUE, model selection and quantity selection of all key equipment are completed at a time; professional splitting, repeated adjustment and modification and capacity redundancy caused by traditional serial design are avoided, the design period is remarkably shortened, and initial investment is reduced.

The utility model discloses an efficient cooling-water machine which comprises a machine shell, and an installation cavity is formed in the machine shell. The water tank is provided with a water return connector and a water outlet connector. The heat exchanger is provided with a first heat exchange pipe and a second heat exchange pipe, one end of the first heat exchange pipe is communicated with the water return connector, and the other end of the first heat exchange pipe is communicated with a pipeline of external equipment; the refrigeration assembly comprises a compressor, a condenser, a drying filter and a capillary tube, an outlet of the compressor communicates with an inlet of the condenser, an outlet of the condenser communicates with an inlet of the drying filter, an outlet of the drying filter communicates with one end of the capillary tube, and the other end of the capillary tube communicates with one end of the second heat exchange tube. The other end of the second heat exchange pipe communicates with an inlet of the compressor. Heat exchange between water in the water tank and a refrigerant is achieved through the first heat exchange pipe and the second heat exchange pipe of the heat exchanger, cooling is conducted through cold water in the water tank, and the cooling amount and the cooling efficiency are improved.

The invention relates to an urban rail transit station ventilation and air conditioning system cooperative control method, device and equipment based on dynamic energy efficiency optimization and a medium. Constructing an energy efficiency model of the ventilation and air conditioning system by combining the energy efficiency curved surface characteristics of the water chilling unit and the cubic law power consumption characteristics of the frequency conversion equipment; an intelligent optimization algorithm is adopted, a dynamic scaling temperature feasible domain of chilled water of a water chilling unit and a frequency interaction limitation domain of frequency conversion equipment are constructed, the feasibility of a temperature set value is kept, meanwhile, coupling constraints in the frequency conversion equipment are decoupled, and an optimal parameter combination is solved; and the optimal parameter combination is issued to an execution layer, the actual energy efficiency ratio deviation of the system is monitored in real time, and energy efficiency model parameter re-calibration or iterative optimization is triggered according to a deviation threshold. Therefore, the overall energy efficiency of the ventilation air conditioning system is stably improved, and efficient operation under the dynamic working condition is achieved.

The invention relates to the technical field of power generation system transformation, in particular to an energy storage power generation system and method based on thermal power plant transformation. The Carnot battery unit comprises a liquid carbon dioxide storage tank, an electric heater, a compressor, a heat storage transducer heat flow channel and an expansion machine which are connected in sequence, and the liquid carbon dioxide storage tank adopts a boiler drum of a thermal power plant and stores liquid carbon dioxide liquefied by a water chilling unit of the thermal power plant; the heat storage circulating unit exchanges heat with a heat flow channel of the heat storage transducer to store heat; the steam power generation unit adopts a thermal power plant steam generator set and extracts heat stored by the heat storage circulation unit for steam power generation. The thermal power generating unit is transformed into the carbon dioxide Carnot battery energy storage system, the defect that a power grid is unstable in the process that a traditional thermal power plant is gradually converted into new energy is overcome, double stable output electric quantity is achieved, the system efficiency is improved, and meanwhile high economic benefits are achieved.

The utility model discloses a multi-system water chilling unit which comprises at least two heat exchange systems, at least two waterway systems and a combined heat exchanger, and the heat exchange systems can be combined to form or respectively form an independent heat exchange circulation loop by switching the serial or parallel connection state and the opening or closing state of the combined heat exchanger; the water path system can be combined to form or respectively form an independent water circulation loop, so that the heating or refrigerating capacity of the unit is obviously increased; different heat exchange circulation loops are switched and controlled by adjusting refrigerant flowing paths between the multiple heat exchange systems and the combined heat exchanger, and different water circulation loops are switched and controlled by adjusting water medium flowing paths of the multiple water path systems. Therefore, after the water chilling unit is installed, different operation modes can be selected and switched according to different heat or cooling capacity requirements, hot water or cold water with the corresponding capacity and temperature is produced, the heating or cooling capacity of the unit is matched with the actual requirement, the whole equipment or part of elements do not need to be replaced, cost is low, and maintenance is convenient.

The invention belongs to the technical field of storage and charging equipment, and particularly relates to a storage and charging all-in-one machine which comprises a shell cooling mechanism, the interior of a shell is divided into a battery bin and an inversion bin, a battery module is arranged in the battery bin and comprises a plurality of stacked battery cells, an alternating-current and direct-current inverter is arranged in the inversion bin, and the battery cells are connected with the alternating-current and direct-current inverter. And the AC / DC inverter is electrically connected with the battery module. According to the invention, a closed-loop liquid cooling circulation system is adopted, heat conduction liquid can rapidly take away heat when the battery cell works, performance degradation or potential safety hazards of the battery cell caused by too high temperature are avoided, the heat dissipation area is increased through the design of the circuitous and surrounding insulating heat conduction pipe, and the cooling efficiency is obviously higher than that of a traditional air cooling scheme in cooperation with constant temperature control of the industrial water cooler. The shell is divided into the battery bin and the inverter bin, the battery module and the alternating current and direct current inverter are arranged in a partitioned mode, mutual interference of heat generated when the battery and the inverter work can be properly avoided, maintenance of all parts is facilitated, and the operation stability of equipment is improved.

The utility model relates to the technical field of combustion torches, in particular to an internal combustion type biogas torch. Comprising a base, the upper surface of the base is fixedly connected with a torch cylinder and an automatic ignition system, the torch cylinder is arranged on the outer side of the automatic ignition system in a sleeving mode, one side of the torch cylinder is fixedly connected with an air inlet pipe, one end of the air inlet pipe is fixedly connected with the automatic ignition system, and the middle section of the air inlet pipe is provided with a dehumidification mechanism. When marsh gas is injected into the torch barrel through the gas inlet pipe for combustion, the cooling-water machine is started to cool the wall of the U-shaped pipe, and when the marsh gas in the water inlet pipe flows through the surface of the U-shaped pipe, water vapor in the marsh gas is condensed on the wall of the U-shaped pipe, so that the water vapor in the marsh gas is filtered out, and the combustion efficiency of the marsh gas is improved; meanwhile, after biogas is introduced into the gas inlet pipe, the U-shaped pipe vibrates in multiple directions, condensate water on the surface of the U-shaped pipe is vibrated to fall into the water tank, and the situation that the residual condensate water on the surface of the U-shaped pipe evaporates again, and water vapor is mixed into the biogas again is avoided.

The invention relates to the technical field of printing equipment, in particular to a printing ink drying device for anti-counterfeiting stained paper, which comprises a rack, a conveying mechanism is arranged above the rack, a drying box body is arranged above the conveying mechanism, and the drying box body is sequentially divided into a leveling preheating area, a main curing area and a forced cooling area along the conveying direction; the conveying mechanism comprises a high-temperature-resistant conveying mesh belt and a vacuum adsorption platform arranged below the mesh belt; an LED-UV cold light source assembly is arranged in the main curing area, infrared heating pipes transversely arranged in the leveling preheating area and a reflecting cover above the infrared heating pipes are matched with the LED-UV cold light source assembly with a water-cooling circulation flow channel in the main curing area and an external cooling-water machine, and printing ink is evenly heated through infrared radiation to be leveled firstly; curing is completed through low-temperature ultraviolet light, a light source is cooled synchronously in a circulating mode, the effects of ink flat curing and paper low-heat deformation are achieved synchronously, and high-speed continuous operation is effectively supported.

The invention relates to the technical field of general control systems, in particular to a water chilling unit energy-saving control method and system.The method comprises the steps that the machining process of a numerical control machine tool is equally divided into a plurality of monitoring time periods, and the demand degree of a water chilling unit in the machining process of the numerical control machine tool in the monitoring time periods is determined to screen out a target monitoring time period; energy consumption of the water chilling unit in the target monitoring time period is determined in combination with the time interval from the moment after the cutting temperature rises to the moment when the rotating speed of the compressor changes, and then the cooling effect of the water chilling unit in the target monitoring time period is determined in combination with rising changes of the cutting temperature and the environment temperature. And determining a regulation and control coefficient of the variable frequency driving control system in the target monitoring time period, and regulating and controlling the running speed of a compressor of the water chilling unit. The regulation and control coefficient for energy-saving control of the water chilling unit in the frequency conversion control system is obtained, and the operation speed of the compressor of the water chilling unit is regulated and controlled, so that the purpose of energy-saving control of the water chilling unit is achieved.

The invention relates to the field of equipment control, in particular to an equipment energy-saving control system and method based on an AI large model, and the system comprises an equipment sensing module, a load prediction module, a fuzzy control module, a wind-water joint debugging module and an energy efficiency optimization module, the equipment sensing module is used for determining the thermal gain in a region, the load prediction module is used for generating a pre-control decision, and the fuzzy control module is used for generating a fuzzy control result; the fuzzy control module is used for calculating static pressure and air supply volume, the air-water joint debugging module is used for correcting the air supply volume of each area, and the energy efficiency optimization module is used for planning the refrigerating capacity supply efficiency of the air conditioner in different time periods. The stable operation of equipment such as an air-conditioning compressor, a water pump and a fan is guaranteed; the reliability of an energy-saving control system is enhanced; the energy consumption cost of building operation is reduced; and the comprehensive energy efficiency of an air-conditioning system is improved.