6174 results about "Cooling tower" patented technology

The invention discloses a central air-conditioning system optimization control method oriented to building load prediction, which comprises the following steps: building a building load prediction model based on a long short-term memory network, combining real-time acquired building electrical load, indoor and outdoor temperature, humidity and equipment operation power data to accurately predict building cooling load requirements in a future time period, and on this basis, optimizing a central air-conditioning system. According to the method, time-of-use electricity price information is used for dynamically adjusting a cooling capacity distribution strategy of the central air conditioning system, so that the energy consumption and the operation cost of the system are reduced to the maximum extent while the load requirement is met. Compared with the prior art, the method has the advantages that the problems of insufficient load fluctuation response and insufficient energy consumption optimization are effectively solved, and the operation efficiency and economical efficiency of the central air-conditioning system of the building can be remarkably improved.

The invention belongs to the technical field of intelligent control of heating, ventilation and air conditioning systems, and particularly relates to an intelligent optimizing and energy-saving control method for a central air conditioner based on deep learning, which comprises the following steps of: acquiring operation data of a central air conditioning system in real time through an internet of things technology; the operation data comprises operation parameters of cold and heat source equipment, flow and lift parameters of a water pump, fan frequency parameters of a cooling tower, temperature and humidity data of an air conditioner terminal, environment temperature and humidity data, weather forecast data and the like. Through deep integration of Internet of Things perception, deep learning prediction and a multi-objective optimization technology, the limitation of a traditional control framework is broken through, meanwhile, accurate prediction of building cooling and heating loads is realized through construction of a hybrid deep learning model, an optimization objective of a full life cycle perspective is established in combination with an equipment performance degradation model, and the system performance is improved. A federal learning framework is innovatively introduced into region-level energy efficiency management, and the model generalization ability is improved on the premise of ensuring data privacy.

The invention discloses a central air conditioner energy-saving optimization system based on load prediction, and relates to the technical field of air conditioner energy saving.According to the central air conditioner energy-saving optimization system based on load prediction, a VMDTransformerGRU hybrid deep learning model is introduced, through multi-source data fusion, the precision of cold load prediction is remarkably improved, and the prediction model can recognize the load change trend in advance. According to the improvement, the dynamic response capacity of the system is effectively enhanced, pre-regulation and control can be carried out before load changes, energy waste is reduced, a water chilling unit, a cooling tower and a pump are modeled to be independent intelligent agents, multi-agent deep reinforcement learning (MADRL) is adopted, and all the intelligent agents can autonomously learn and optimize control strategies of the intelligent agents. The intelligent agents cooperate with one another, efficient operation of the whole system is achieved through autonomous decision, and operation conflicts between devices are avoided. In this way, dynamic coordination and joint optimization among all the devices are achieved, invalid energy consumption is reduced, and the overall energy-saving effect and operation stability of the system are remarkably improved.

The invention relates to an ice crystal evaporator and an ice crystal water cooling device producing from the same, belonging to the technical field of refrigeration. The ice crystal evaporator is characterized in that a liquid inlet channel is formed by an evaporator tube, a liquid inlet and a liquid outlet in a tubular casing; and the outer channel of the evaporator tube of the tubular casing is divided into more than one S-shaped channel forming a water return channel through a water inlet of a water divider and a water outlet of a water collector. The ice crystal water cooling device is characterized in that the return air inlet of the ice crystal evaporator is communicated with a compressor, a condenser, a liquid feeding valve, a dry filter, a liquid feeding electromagnetic valve anda thermostatic expansion valve in sequence, and then is communicated with the liquid inlet of the ice crystal evaporator; a cooling water inlet / outlet of the condenser is connected with a cooling tower in series; and a water inlet / outlet of the ice crystal evaporator is communicated with a water circulating pump and an ice crystal energy storage tank in series. The invention has the advantages ofhigh cooling efficiency, no icing and low cooling temperature and is suitable for production of energy storage central air-conditioning, marine fishing, seafood processing, fruit, vegetable or meat processing, and the like; the cooled medium is municipal water.

The invention discloses a mass concrete intelligent temperature monitoring system and method, and the system comprises a high-precision temperature sensor, a data collection node which is connected with the high-precision temperature sensor and is responsible for carrying out the primary processing and integration of temperature data collected by the sensor, and a data collection terminal which serves as a data convergence center of the whole monitoring system and is used for collecting the temperature data. The intelligent temperature monitoring system comprises a plurality of data acquisition nodes which are connected in a wired or wireless communication mode, a data monitoring platform which operates at a server end and is a core control and management unit of the whole intelligent temperature monitoring system, and a circulating water cooling control system which is composed of a cooling water pump, a cooling tower, a cooling water pipe network, a temperature control main station and the like. The cooling water pipe network is embedded in the concrete in advance to form a closed water circulation loop; the temperature control master station receives a cooling control instruction sent by the data monitoring platform, and adjusts the rotating speed of a cooling water pump and the working state of a cooling tower according to the instruction, so that the flow and temperature of cooling water in a cooling water pipe network are accurately controlled; through flowing of circulating water in the concrete, redundant heat in the concrete is taken away, effective regulation and control over the temperature in the concrete are achieved, key indexes such as the highest temperature and the temperature gradient of the concrete are controlled within a reasonable range all the time, and concrete cracks caused by temperature stress are avoided.

The invention provides an intelligent monitoring system of a liquid cooling cabinet and processing equipment thereof, and relates to the technical field of data processing, and the system comprises a cold source self-control module which is used for dynamically adjusting the operation state of a cooling tower of primary side circulation and the flow of a circulating water pump according to cooling water parameters, and achieving the variable flow control of cooling water; the dynamic environment monitoring module is used for monitoring the secondary side pipeline state and the cabinet environment in real time through the cooling capacity distribution unit and the distributed sensor network; and the comprehensive monitoring sub-module is used for realizing leakage positioning through a built-in liquid leakage sensor, a temperature sensor and a pressure sensor, and automatically supplementing liquid by using a liquid storage tank. Through multi-mode sensor fusion, dynamic threshold value self-adaption and multi-parameter collaborative analysis, accurate leakage positioning and graded alarm are achieved, automatic liquid supplementing closed-loop control and variable flow adjustment are combined, the system reliability is improved, and energy consumption is reduced.

The invention discloses an energy consumption optimization control method and system for heating and ventilation equipment, and the method comprises the steps: carrying out the comprehensive evaluation of the energy consumption condition of the heating and ventilation equipment, and recognizing the current energy consumption condition and energy-saving potential of the equipment; the system is connected with heating and ventilation equipment through the Internet of Things technology, and collects parameters of the heating and ventilation equipment in real time. Based on the preprocessed data, establishing energy consumption models of the water chilling unit, the cooling tower, the freezing pump and the cooling pump; building an energy consumption prediction regression model by adopting a decision tree algorithm, and predicting the total energy consumption of the heating and ventilation system in real time; according to the predicted energy consumption data, an optimization control strategy of the heating and ventilation equipment is formulated in combination with a set energy consumption control objective function; and applying the formulated optimization control strategy to the heating and ventilation equipment, carrying out real-time monitoring and feedback, and carrying out iterative optimization on the control strategy according to an actual effect. According to the method, comprehensive evaluation, real-time monitoring and optimal control of the energy consumption of the heating and ventilation equipment can be realized, and a powerful guarantee is provided for energy conservation and emission reduction of a building.

The invention discloses a cold station multi-equipment combination energy efficiency optimization method and system, relates to the field of cold station energy efficiency optimization, and aims to solve the problems of low energy efficiency and response lag caused by manual adjustment. The method comprises the following steps: S1, acquiring key operation data (power, state, temperature, flow and frequency) of a water chilling unit, a cooling tower and a water pump and external environment data (temperature and humidity, wind speed and load prediction) in real time; s2, constructing an equipment energy efficiency model based on historical data, and quantifying the change of the equipment efficiency along with the load rate, the temperature difference and the environment temperature; s3, according to the current load and environment prediction, simulating and traversing the energy consumption of the equipment start-stop combination and the water pump frequency combination by applying a Monte Carlo algorithm, and screening a combination strategy with the lowest total energy consumption of the system; s4, converting the optimization strategy into a control instruction, and issuing the control instruction to equipment for execution; and S5, comparing the actual energy consumption with the predicted value, and if the deviation exceeds 5%, correcting model parameters by adopting a least square regression algorithm to realize closed-loop optimization. And the energy efficiency and the response speed of the cold station are obviously improved.

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 relates to a gas leakage early warning method and system for a chemical industry park. The early warning method comprises the following steps: acquiring real-time temperature and pressure data of a reaction kettle area and a storage tank area; obtaining a historical leakage record of a pipeline joint, and determining a diffusion path prediction boundary; extracting a wind direction and a wind speed in a diffusion path prediction boundary, and determining space-time distribution characteristics; analyzing space-time distribution characteristics, determining an overlapping region and setting concentration monitoring nodes; identifying the concentration contribution ratio of the reaction kettle area diffusion characteristic and the storage tank area diffusion characteristic; integrating the operation data of the pipeline joint diffusion characteristics and the loading and unloading area diffusion characteristics, and determining a diffusion path deviation correction coefficient; combining the deviation correction coefficient with the humidity data of the peripheral diffusion characteristics of the cooling tower; and updating diffusion parameters of the separation tower area diffusion characteristics and the public engineering area diffusion characteristics according to a source intensity estimation result. According to the invention, accurate prediction and early warning of gas diffusion in a complex chemical device area are realized, and the safety management level is improved.

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.

According to the cooling tower early fault early warning method based on vibration state monitoring, vibration signals and working condition labels of key parts of the cooling tower are synchronously collected through multiple channels, and data quality is improved through preprocessing operation such as band-pass filtering and normalization; time-frequency features are extracted in a multi-scale mode through self-adaptive variational mode decomposition and wavelet packet transformation, signal complexity is quantized through energy entropy, and weak fault detection capacity is enhanced; the obtained features are input into a deep belief network after being subjected to principal component analysis dimensionality reduction, and automatic classification and recognition of the equipment operation state are achieved; dynamic early warning grade adaptation is carried out according to an identification result in combination with a working condition label, the environmental adaptability and stability of early warning are effectively improved, the method further has the functions of early warning sample recording and periodic model iterative optimization, and the fault identification precision and robustness in a complex noise environment are remarkably improved.

The invention relates to the technical field of industrial control, and discloses a dry-wet combined cooling tower operation state prediction and diagnosis system comprising a load prediction module used for obtaining production plan data and environment information, constructing a basic heat load prediction model, and outputting a total prediction heat load; the thermal modeling module is used for establishing a heat transfer model and an energy consumption model, the heat transfer model outputs cooling amounts in different operation modes, and the energy consumption model outputs total predicted power; the dry-wet decision module is used for constructing a multi-objective optimization function and solving the multi-objective optimization function to obtain a dry-wet switching strategy; and the control execution module is used for executing the dry-wet switching strategy. According to the method, the basic thermal load prediction model is established, so that the prediction precision of the thermal load is improved, and differentiated cooling strategies are provided for different production stages; on the basis of real-time load requirements and environmental conditions, a dry mode or a wet mode is intelligently selected for operation, and a multi-objective optimization function is constructed, so that the balance between cooling requirement meeting and system energy consumption minimization is realized.

The invention relates to a cooling tower device for recovering heat from waste steam, which adopts three layers of transversely arranged heat exchange tube groups, realizes cascade recovery of heat energy of waste steam through communication of an air inlet and an air outlet, and is additionally provided with fins on the surfaces of heat exchange tubes to enhance the gas-liquid mass transfer efficiency. The core innovation lies in that a built-in mechanical cleaning mechanism is arranged, a driving assembly is in linkage with multiple sets of bidirectional adapters through a rotating shaft, brush rods distributed in the circumferential direction are driven to conduct high-frequency physical scraping on heat exchange pipes and fins, scale deposition is effectively restrained, and compared with traditional chemical cleaning, the shutdown maintenance time is shortened; the steam latent heat recovery rate can be increased, meanwhile, secondary pollution is avoided through a full-mechanical cleaning scheme, modular layout is adopted in structural design, interlayer fluid distribution of the heat exchange pipe set is achieved through a U-shaped pipe and a straight pipe, it is ensured that the resistance coefficient of the system is lower than that of similar equipment, and the device has remarkable energy-saving benefits in industrial scenes such as chemical engineering and metallurgy.

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 data center energy control, and discloses a data center cooling system dynamic control method adaptive to equipment aging, and the method comprises the steps: firstly constructing an energy consumption model for controlling a data center cooling system based on equipment parameters and an energy conservation principle; in order to solve the problem of performance degradation possibly caused by long-term operation of equipment, the method monitors operation parameters of key equipment such as a cooling tower, a heat exchanger, a water chilling unit and an air conditioner terminal in real time; according to the method, an equipment energy consumption model is iterated in a rolling manner by using a long-short term memory (LSTM) network model in deep learning, so that the energy consumption model for control is dynamically updated, the prediction precision is improved, and finally efficient model prediction control is realized. The method is not only suitable for the design and construction of a new data center, but also suitable for the transformation and upgrading of an existing data center, and has wide application prospects and practical values.

The invention discloses a circulating water temperature control method and system for thermal power generation, and relates to the related technical field of thermal power generation, and the method comprises the steps: collecting real-time monitoring data of condenser outlet water temperature, cooling tower inlet water temperature and environment temperature and humidity data, and generating a dynamic thermodynamic feature set; dynamic compensation analysis is conducted by combining the unit load fluctuation rate and the cooling tower fan rotating speed; according to the temperature gradient change of the circulating water, temperature control deviation is used for correction; cooling water circulation control is conducted on a circulating water system of thermal power generation by predicting the cooling water amount adjusting amount, predicting the temperature overshoot risk level and configuring a control instruction set. The technical problems that in the prior art, due to the fact that a circulating water temperature control model is insufficient in precision and a control strategy lacks dynamic adaptability, the circulating water temperature control precision is insufficient, and the risk cannot be effectively estimated are solved, the temperature overshoot risk is early warned in advance, and the technical effect of improving the accuracy of power generation circulating water temperature control is achieved.

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 discloses a cooling tower fault tracing method based on a knowledge graph, and the method comprises the steps: collecting all kinds of operation, fault symptoms and environment condition data of a cooling tower in a distributed manner, carrying out the abnormal value processing, missing completion and normalization, and constructing a knowledge graph which takes equipment components, fault modes and symptoms as nodes and causes and effects and association as edges; a fault propagation path is generated in a knowledge graph by using a structured symptom vector, a semantic feature and a historical statistical feature are combined to dynamically evaluate a path weight, and multi-round iterative optimization and sorting are realized, so that a key path with a significant weight is identified as a final fault traceability basis, and a maintenance decision is further supported. According to the invention, the traceability accuracy of complex faults of the cooling tower and the adaptive capability of the knowledge graph are effectively improved.

The invention discloses a fan driving motor ground insulation evaluation method and device, and the method comprises the steps: inputting an effective value of a common-mode leakage current signal of a fan driving motor into a constructed fan driving motor ground insulation impedance evaluation model 1, and obtaining a first evaluation result; inputting a vibration speed signal of the fan driving motor into the constructed fan driving motor ground insulation impedance evaluation model 2 to obtain a second evaluation result; inputting the first evaluation result and the second evaluation result into a constructed fan driving motor ground insulation impedance fusion evaluation model to obtain a third evaluation result; and inputting the third evaluation result and a corresponding principal component obtained by the AC voltage signal into a constructed fan driving motor ground insulation decoupling model to obtain the resistance value of a fan driving motor ground insulation resistor and the capacitance value of a fan driving motor ground insulation capacitor. According to the invention, on-line monitoring of the ground insulation of the driving motor of the cooling tower fan of the phase modifier is realized, and the detection precision of the ground insulation of the driving motor of the cooling tower fan of the phase modifier is improved.

The invention relates to the field of central air-conditioning systems, in particular to a full-recovery water source heat pump central air-conditioning system. The ground source heat pump system solves the technical problems that when a ground source heat pump system in the prior art is used in a region where the difference between the refrigerating duration in summer and the heating duration in winter is large, the heat exchange capacity of a buried pipe is gradually attenuated along with the duration, so that the refrigerating and heating effects are affected, and the installation limitation of the ground source heat pump system is obvious when the buried pipe system is installed. According to the technical scheme, the full-recovery water source heat pump central air-conditioning system comprises a temperature generation module, a heat exchange module, a heat exchange module, an auxiliary refrigeration module, a cooling module, a water supply module and an auxiliary heating module; auxiliary is carried out during refrigeration and heating in an auxiliary refrigeration and auxiliary heating mode, the heat exchange efficiency of the system is improved, heat exchange is carried out on high-temperature water generated by a main machine through multiple sets of heat exchange structures, air conditioner energy consumption is reduced, the cooling tower structure can be miniaturized, and therefore the limitation of the system during installation and construction is reduced, and the cost is reduced. And the application range of the system is expanded.

A system includes a cooling tower, an algae inhibitor skid, and at least one pump fluidly connected between the cooling tower and the algae inhibitor skid. The algae inhibitor skid includes a first water tank containing a first water supply fluidly connected to the cooling tower and barley straw suspended within the first water tank above the first water supply.

A cold source integration device, a heat dissipation system, a controller and a heat dissipation control method, relating to the technical field of heat dissipation. The cold source integration device is connected to an air-liquid heat exchange mode assembly by means of a liquid cooling pipeline and connected to a liquid-liquid heat exchange mode assembly by means of the liquid cooling pipeline, the air-liquid heat exchange mode assembly and the liquid-liquid heat exchange mode assembly being connected by means of the liquid cooling pipeline. The cold source integration device is used for providing a cooling liquid by means of the liquid cooling pipeline, the cooling liquid successively passing through the air-liquid heat exchange mode assembly used for dissipating heat of a first device of an apparatus and the liquid-liquid heat exchange mode assembly used for dissipating heat of a second device of the apparatus; the cold source integration device is further used for receiving the cooling liquid output after heat of the second device is dissipated. The device meets the requirements of different liquid cooling modes on temperature by supplying one path of cooling liquid, decreases the number of cooling liquid supply lines, and decreases the number of cooling towers, the number of circulation pumps and the number of liquid cooling pipelines, thus greatly reducing system complexity.

The invention discloses a zero-emission combined treatment method and device for high-salinity wastewater and circulating water, and relates to the field of water treatment.The method comprises the steps that 1, the circulating water and the high-salinity wastewater in a water collecting tank of an open cooling tower enter a diaphragm electrolytic cell for electrochemical softening treatment; (2) carrying out carbon dioxide micro-nano bubble treatment on water discharged from the cathode chamber, then carrying out sedimentation treatment, and returning the treated water to the open cooling tower water collecting tank; (3) monitoring the water quality of the circulating water and the high-salinity wastewater in real time, and discharging the circulating water and the high-salinity wastewater into a closed cooling tower water collecting tank when a discharge condition is met; (4) carrying out reverse scale precipitation treatment on the spray circulating water by using a nanocrystalline material, wherein the closed cooling tower runs under the limit concentration multiple and does not discharge water; and (5) the closed cooling tower sprays circulating water to evaporate and exchange heat, and precipitated scaling particles and crystallized salt particles are discharged after being deposited. Specific components in the high-salinity wastewater are selectively consumed to replace chemicals to remove hardness and obtain a chlorine byproduct, so that high-value utilization of the high-salinity wastewater is realized, and salt reduction and corrosion reduction effects in a downstream process are achieved.

The invention provides a cooling tower optimization control method and device of a central air-conditioning system, a terminal and a medium. The method comprises the steps that the wet bulb approximation degree of a cooling tower and the comprehensive energy efficiency of the central air-conditioning system in the current environment are obtained; according to the wet bulb approximation degree, determining a corresponding to-be-optimized control strategy of the cooling tower when the power consumption value of the cooling tower is the lowest; and the control strategy to be optimized is optimized by adjusting the modulation coefficient of the cooling tower model and the interaction information of the cooling tower and the adjacent cooling tower, and the optimized control strategy is executed so that the comprehensive energy efficiency of the central air conditioning system at the current moment can be maintained to be larger than or equal to the comprehensive energy efficiency at the previous moment. The wet bulb approximation degree is calculated by considering the influence of the air relative humidity, the wind speed synergistic effect and the dynamic change of the cooling tower load rate on the wet bulb temperature, the control strategy is determined, and the control strategy is further optimized and executed by modulating the interaction information of the cooling tower model and the parallel cooling towers. Therefore, the comprehensive energy efficiency of the central air-conditioning system is improved and maintained.

The invention discloses a cold source integration device, a heat dissipation system, a controller and a heat dissipation control method, and relates to the technical field of heat dissipation, the cold source integration device is connected with an air-liquid heat exchange mode assembly through a liquid cooling pipeline and connected with a liquid-liquid heat exchange mode assembly through a liquid cooling pipeline, and the air-liquid heat exchange mode assembly and the liquid-liquid heat exchange mode assembly are connected through the liquid cooling pipeline. The cold source integration device is used for providing cooling liquid through the liquid cooling pipeline, the cooling liquid sequentially passes through an air-liquid heat exchange mode assembly used for dissipating heat of a first device of the equipment and a liquid-liquid heat exchange mode assembly used for dissipating heat of a second device of the equipment, and the cold source integration device is further used for receiving the cooling liquid output after the second device is subjected to heat dissipation. According to the device, by supplying one path of cooling liquid, the requirements of different liquid cooling modes for the temperature are met, the number of cooling liquid supply lines is reduced, the number of cooling towers, the number of circulating pumps and the number of liquid cooling pipelines are reduced, and the system complexity is greatly reduced.

The invention discloses a hydrophilic material and a hydrophobic material, a preparation method of the hydrophilic material and the hydrophobic material, and a gas-liquid separation filtering device equipped with the hydrophilic material and the hydrophobic material, the hydrophilic material comprises a substrate surface which is etched into a micro-nano structure, and a hydrophilic layer is formed on the surface of the substrate; the hydrophobic material comprises a base material and a hydrophobic layer, the surface of the base material is etched into a micro-nano structure, and the hydrophobic layer is formed on the surface of the base material; the windward side of the filtering device for gas-liquid separation is made of a hydrophilic material, the air outlet side of the filtering device for gas-liquid separation is made of a hydrophobic material, the hydrophilic material and the hydrophobic material can be folded surfaces or curved surfaces, and water gathered by the hydrophilic material and water intercepted by the hydrophobic material are recycled through water guide holes; the hydrophilic material is formed by carrying out surface plasma treatment activation on a base material and carrying out surface polymerization modification on a hydrophilic monomer; the hydrophobic material is prepared from a base material through surface plasma treatment activation and hydrophobic monomer surface polymerization modification. According to the cooling tower, the heat dissipation and cooling performance of the cooling tower can be guaranteed while the water resource recycling efficiency is guaranteed.

The invention discloses a cooling tower operation state monitoring method and system based on big data analysis, and relates to the technical field of data processing, and the method comprises the steps: obtaining water temperature data of an inlet and an outlet of a cooling tower, calculating a cooling temperature difference, and carrying out the cooling efficiency evaluation based on a time sequence temperature relation; analyzing the relationship between the control parameters of each level of the cooling tower in combination with historical operation data and a field big data sample, and establishing a level control analysis path; and on the basis of the cooling target of the heat source equipment, analyzing control parameters of each level through the time sequence cooling efficiency, identifying the running state of the cooling tower, and sending state feedback information. The technical problems that existing cooling tower operation state monitoring depends on simple static measurement, dynamic optimization and real-time adjustment of control parameters of all levels are lacked, and the operation efficiency of the cooling tower is affected are solved, and the purposes that the control parameters are dynamically optimized in real time through big data analysis and multi-level control analysis, and the operation efficiency of the cooling tower is improved are achieved. And the operation efficiency of the cooling tower is improved.

The utility model discloses a double-source coupling type heat pump system which comprises an air source heat pump unit, a water source heat pump unit, an energy storage water tank, a water storage tank, a cooling tower and a heat consumer, and a first circulation pipeline, a second circulation pipeline, a third circulation pipeline and a fourth circulation pipeline are respectively formed through opening and closing control of a plurality of electromagnetic valves to achieve different operation modes. Switching of a single-source system and a double-source system and multiple heating (cooling) modes can be achieved. During coupling operation, the double-source heat pump unit and the water tank form a first circulation pipeline. During decoupling operation, the low-temperature air source heat pump unit is directly communicated with the heat user to form a second circulating pipeline; the low-temperature air source heat pump unit, the energy storage water tank and the heat user form a third circulating pipeline to realize heating (cooling); the water source heat pump unit, the energy storage water tank, the cooling tower and the heat user form a fourth circulation pipeline to refrigerate the heat user.

The utility model relates to the technical field of cooling towers, and discloses a uniform water distribution device for a cross-flow cooling tower, which comprises a water storage tank, a water distribution disc, a water outlet pipe and a water distributor, the water storage tank is positioned above the water distribution disc, a plurality of through holes are formed in the bottom of the water storage tank, and a plurality of water distribution holes are formed in the bottom of the water distribution disc; the water segregator comprises water segregation main pipes, diversion joints and a plurality of water segregation branch pipes, the water segregation main pipes are connected to the water outlet pipes in a one-to-one correspondence mode, the water segregation main pipes and the water segregation branch pipes are connected through the diversion joints, the ends, away from the diversion joints, of the water segregation branch pipes are closed, and a plurality of water segregation holes are formed in the bottoms of the water segregation branch pipes. Water in the water storage tank enters the water distribution main pipe along the water outlet pipe, then is distributed to the water distribution branch pipes through the flow distribution connectors, and then is distributed through the water distribution holes of the water distribution branch pipes. Water falls into the water distribution disc from the water distribution holes and then is distributed through the water distribution holes; water distribution is performed after primary water distribution, so that water distribution is more continuous and uniform.