4035 results about "Cooling tower" patented technology

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 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 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 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 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 invention belongs to the technical field of cooling towers, and particularly relates to a circulating spraying system and a cooling tower comprising the same, the circulating spraying system comprises a water pipe, a water tank arranged below the water pipe; the pressure control assembly is arranged in the water tank and comprises a sealing block, a connecting ring is arranged on the outer surface of the sealing block, and a connecting hole is formed in the lower surface of the connecting ring. During use, the water pump is started to feed water in the water tank into the atomizing nozzles through the water conveying pipe and the flow dividing pipe. Water flow firstly makes contact with the flow guide strips, impacts the flow guide pieces after drainage and drives the connecting plate and the transmission rod to rotate. The transmission rod penetrates through the first linear bearing and is matched with the second linear bearing to drive the cleaning support to rotate, the first spring buffers, the second spring pushes the cleaning support to enable the cleaning brush to be attached to the inner wall of the nozzle, and the inner wall is cleaned rotationally. After passing through the kinetic energy conversion assembly, the water flow is atomized and sprayed out through the spray orifice plate. The flexible nanofiber brush can remove dirt to avoid blockage, the inner wall is not damaged, and uniform atomization is guaranteed.

The invention discloses a heat allocation system based on a heat pump. The heat allocation system comprises a water tank; a water source heat pump; an air source heat pump; a cooling tower; a cooling water circulation system; a hot water circulation system; a chilled water circulation system; an exhaust heat recovery system; wherein the water tank, the water source heat pump, the air source heat pump, the cooling tower, the cooling water circulation system, the hot water circulation system, the chilled water circulation system and the exhaust heat recovery system are connected with one another to realize heat allocation, especially heat allocation of a coating pretreatment electrophoresis production line of a vehicle body or parts forming the vehicle body; according to the system, heat generated when the heat pump / refrigerating unit produces chilled water and / or heat taken away in exhaust air can be recycled and used for heating the heat using tail end. Therefore, the heat which is wasted originally can be fully utilized, the energy consumption is reduced, and the utilization efficiency of energy is improved.

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 invention provides a circulating blow-down water treatment device and process based on a crystallization and granulation fluidized bed coal-fired power plant. The device comprises a cooling tower pool, a multi-medium filter, a crystallization and granulation fluidized bed, a circulating blow-down water buffer pool, a high-density clarification pool, a plug flow channel, a variable-porosity filter pool, a clarification water pool, a self-cleaning filter, an ultrafiltration device, an ultrafiltration water tank, an ultraviolet sterilizer, a security filter and a reverse osmosis device which are connected in sequence. According to the scheme, by introducing induced crystallization for hardness removal and synergistic silicon removal, deep precision treatment can be performed on the circulating sewage, quality-divided recycling is realized, and gradient utilization of water resources is realized; in addition, in the treatment process, the use of chemicals polluting the environment is reduced, the entry of chlorine radicals is avoided, and the great increase of the amount of the recycled desulfurization wastewater is effectively reduced.

The utility model discloses a variable flow water distribution mechanism for a cooling tower, which comprises a cooling tower body, a vertical metal pipe is arranged in the cooling tower body, the top of the metal pipe is connected with a cross-shaped connecting steel pipe, the end part of the connecting steel pipe is connected with a spraying frame, and the spraying frame is connected with a water inlet pipe. The outer side of the spraying frame is inserted into the inner wall of the cooling tower body, and electromagnetic valves are installed in the four directions of the connecting steel pipe. Filler is installed in the cooling tower body, and a temperature sensor is installed on the inner wall of the cooling tower body. According to the variable-flow water distribution mechanism for the cooling tower, the electromagnetic valves and the temperature sensors are arranged, the temperatures of different positions in the cooling tower body are detected through the multiple temperature sensors, and then the flow of water entering the corresponding spraying frames is changed through the electromagnetic valves. The situation that more hot water enters a high-temperature place to reduce the heat exchange effect is avoided, the water flow is increased for a low-temperature place, and the overall heat exchange effect is improved.

The invention discloses a dynamic water distribution method and system for a natural ventilation cooling tower, and the method comprises the following steps: testing the natural ventilation cooling tower, obtaining the performance parameters of the cooling tower, constructing a CFD simulation model of the natural ventilation cooling tower, and calculating the performance parameters of the cooling tower according to the CFD simulation model. The performance parameters of the cooling tower serve as boundary conditions of a CFD simulation model of the natural ventilation cooling tower to be calculated, a sample point response value is obtained, a Kriging agent model is constructed, the sample point response value is adopted for training, the trained model is adopted for collecting data of a water distribution execution mechanism of the cooling tower, the data are processed, and the performance parameters of the cooling tower are obtained. And the adjusted initial circulating water flow of the fan-shaped area is obtained, and water distribution adjustment is conducted on a cooling tower water distribution executing mechanism based on the adjusted initial circulating water flow of the fan-shaped area. Dynamic water distribution of the natural ventilation cooling tower according to environmental conditions is achieved, and the influence of environmental crosswind on the heat exchange performance of the natural ventilation cooling tower is reduced.

The invention discloses a centrifugal fan for a cooling tower, and belongs to the technical field of fan equipment, the centrifugal fan comprises a base, the upper end of the base is fixedly connected with a centrifugal fan body, the rear end of the centrifugal fan body is provided with a first motor, the first motor is arranged at the upper end of the base, and the first motor is used for driving the centrifugal fan body; and an air outlet pipe is arranged at the upper end of the centrifugal fan body. Dust is filtered through the arranged filter screen, when the filter screen is cleaned, air flow on one side of the shell can be blocked through the flow separation plate, then the filter screen is cleaned through the cleaning assembly, and therefore during cleaning, dust cannot be subjected to the effect of the air flow and cannot be strongly attached to the upper end of the filter screen, and the dust removal effect is improved. According to the air purifier, dust can be effectively cleaned, the air inlet effect is guaranteed, the filtering assemblies are arranged on the left side and the right side, air can be fed through the other side when one side is cleaned, the machine does not need to be shut down for cleaning, and the using effect is improved.

The intercooling tower shutter control system and method have the characteristics of self-adaption and high precision in the control strategy, the system can automatically adjust the control parameters in the actual operation, and the dependence on manual intervention is reduced. The complexity of operation and maintenance is reduced, and errors and faults caused by manual operation are reduced. And the problem of hysteresis or over-regulation possibly caused by a single controller is effectively avoided. By means of double-layer control, more stable control response can be provided when complex and changeable operation conditions are processed, and system instability caused by environment or load fluctuation is reduced. Through the double-layer fuzzy controller, more accurate temperature adjustment can be realized. The first-layer fuzzy controller is responsible for processing macroscopic temperature and wind speed changes, and the second-layer fuzzy controller is used for further finely adjusting the opening error and the change rate.

The invention discloses a data center low-carbon control method and system, and relates to the technical field of data centers, and the method comprises the steps: collecting the environment parameters and equipment operation data of a data center in a hot-summer and warm-winter region in real time based on a multi-mode sensor network; constructing a climate-adaptive space-time diagram convolutional network, taking a server rack, a cooling tower and a power distribution cabinet as nodes, taking a cold and hot flow path as a dynamic weighted edge, embedding climate feature vectors, and generating a thermal load prediction map; a dynamic refrigeration strategy and a server load migration strategy are generated by taking a thermodynamic equation and a fluid dynamic model as strategy optimization boundary conditions through a physical constraint reinforcement learning framework and combining a thermal load prediction map; and based on the dynamic refrigeration strategy, the air conditioning system is controlled to start a hybrid refrigeration mode according to the real-time climate type, the water cooling main cycle and indirect evaporative cooling standby loop are synchronously operated, and the cold charging and discharging logic of the chilled water storage system is switched according to the electricity price time period.

The invention belongs to the technical field of closed cooling towers, and discloses a countercurrent closed cooling tower and a cooling method.The countercurrent closed cooling tower comprises a tower body, a draught fan is fixedly connected to the top of the tower body, an air inlet is formed in the side wall of the bottom of the tower body, a water collecting tank is formed in the bottom of the tower body, and a pair of coil pipes is fixedly connected to the middle of the tower body; through cooperation of structures such as an annular shell, an annular spraying pipe and a concave panel, the possibility that scale is generated by the coil pipe is reduced, the heat exchange effect can be improved, during heat exchange, water in a collecting groove of the annular spraying pipe moving in a reciprocating mode is pumped and pressurized, the surface of the coil pipe is scoured in an annular mode, and the scale forming risk is reduced; and meanwhile, the sliding columns continuously extrude the wave-shaped grooves, so that the whole annular shell rotates in a reciprocating mode, close-distance washing can be more uniform, and therefore the heat exchange effect and durability of the coil pipe are efficiently improved.

The disclosure relates to a data center cooling system including a cooling tower, an air cooling unit, a liquid cooling unit and a cabinet, the air cooling unit including a first heat exchanger, a fan and an air returning channel, the liquid cooling unit including a second heat exchanger, the cabinet including a server. A coolant outlet of the cooling tower is connected to a coolant inlet of the first heat exchanger and a first coolant inlet of the second heat exchanger, a coolant outlet of the first heat exchanger and a first coolant outlet of the second heat exchanger are connected to a coolant inlet of the cooling tower, a second coolant outlet of the second heat exchanger is connected to a coolant inlet of the server, and a coolant outlet of the server is connected to a second coolant inlet of the second heat exchanger.

The invention discloses a thermal power plant intelligent circulating water energy-saving optimization system control method, relates to the technical field of thermal power plant automatic control, and aims to solve the technical problems of low control precision and large energy consumption of a traditional thermal power plant cold end system and realize optimization control by constructing an intelligent control system based on a Transform deep learning architecture. An intelligent weather data acquisition network is established, meteorological data, satellite meteorological data and a local microclimate sensor network are integrated, and high-precision space-time meteorological information is obtained; according to the method, a Transform encoder-decoder architecture is adopted, multi-source data is converted into a standardized token for representation, and complex association analysis is realized through a multi-head self-attention mechanism; a multi-objective collaborative optimization framework with an objective function as a core is constructed, a steam turbine-condenser-cooling tower-circulating water pump control closed loop is established, and seasonal adaptive control and robust optimization are achieved; providing decision transparent analysis, and explaining a control decision process through attention weight distribution.

The invention belongs to the technical field of locomotive equipment maintenance, and provides an automatic inspection system and method for a locomotive cooling tower, and the method comprises the steps: obtaining the basic information of the locomotive cooling tower, planning an inspection path for an inspection machine, controlling the inspection machine to inspect along the inspection path, and collecting the visual information of the locomotive cooling tower, the method comprises the following steps: constructing a local three-dimensional grid map in real time, detecting obstacles, evaluating a collision risk between the obstacles and an inspection machine, if the collision risk is high, triggering the inspection machine to avoid obstacles, constructing a global three-dimensional grid map when the inspection machine completes an inspection path, and determining an inspection blind area under the global three-dimensional grid map. And judging whether the current inspection time period is ended or not, if not, triggering supplementary inspection, otherwise, planning an inspection path for the next inspection time period, and after the inspection time period is ended, performing anomaly detection and positioning on each part of the locomotive cooling tower based on visual information acquired by an inspection machine through a machine learning algorithm.

The invention relates to the technical field of industrial data storage, in particular to an industrial data storage method and system based on a knowledge graph, and the method comprises the following steps: obtaining cooling tower operation data and binding identification information, constructing a time sequence node and a graph path, extracting a relationship between an attribute tag and a behavior type labeling direction, classification fields belong to path channels in sequence, and structural area additional labels are filled in to write into node relations. According to the method, multi-field synchronous collection is completed through a binding mode of operation data and identification content, an information flow path is constructed according to a time sequence, and paths consistent in sequence are screened according to a field change rule in combination with a transmission direction between attribute labels and behavior type labeling nodes to perform channel division and attribution arrangement. A structural region is filled through unified arrangement of paths and node contents, and label information is added, so that organization association, process continuity and structural logic among data are enhanced, and path stability, node orderliness and data coordination in map construction are improved.