2512 results about "Cooling tower" patented technology

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 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.

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 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 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 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 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 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 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 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.

The invention relates to the field of uranium concentration, and discloses an energy-saving device and method for drying a first-batch centrifugal unit. According to the device, an inlet of a centrifugal machine is connected with an outlet of an evaporator through a pipeline provided with a fourth cooling valve and an eighth cooling valve and is connected to the secondary side of a cooling plate heat exchanger and the secondary side of a heating plate heat exchanger respectively; an outlet of the centrifugal machine is connected with an inlet of the evaporator through a sixth cold valve, a first cold valve and a second water pump. An inlet of the sixth cold valve is connected with the secondary side of the heat supply plate heat exchanger through a first water pump. The primary side of the cold supply plate heat exchanger is connected with a newly-built cooling tower loop, and the primary side of the heat supply plate heat exchanger, the condenser and the newly-built cooling tower form circulation. By optimizing system connection and a heat energy circulation path, the energy utilization efficiency and the equipment utilization rate are effectively improved, and the investment and operation cost is remarkably reduced.

The invention provides a cooling tower floating water loss prediction analysis method, which comprises the following steps: acquiring and cleaning multi-dimensional operation data of a cooling tower, performing working condition label classification, feature normalization and derivative feature extension, and constructing a deep neural network model to realize floating water loss prediction after dynamically adjusting a feature weight based on a working condition classification clustering result. And in the online stage, real-time working condition labels and historical error feedback are combined, and the feature weights and model parameters are dynamically optimized, so that the generalization ability and prediction accuracy of the model under variable working conditions are improved, the engineering applicability and the online adaptive optimization ability are high, and water saving and intelligent operation management of the cooling tower system are effectively supported.

The invention relates to the field of electric power systems, in particular to an energy storage dynamic optimization scheduling method and system of an electric power system and a storage medium, and the method comprises the steps: S1, building an energy storage dynamic calculation model; s3, energy consumption models of a water chilling unit, an air source heat pump, a water pump and a cooling tower are established respectively, and instantaneous energy consumption under different working conditions is calculated by considering operation working conditions and environmental parameter correction; and S4, outputting the utilization rate, the maximum adjusting power, the average adjusting power, the maximum adjusting capacity proportion and the accumulative adjusting electric quantity proportion of the energy storage device, and carrying out quantitative evaluation. According to the method, supply and demand state changes such as valley load, flat load, peak load, peak load and the like of the power system can be identified in real time / quasi-real time, the time periods and power of energy storage and energy release are adjusted, dynamic power distribution of a host in each load time period is realized, and the overall energy efficiency level and operation stability of the system are improved.

The invention discloses an industrial circulating water evaporation water consumption water-saving control method based on artificial intelligence. According to the method, an efficient air cooling device is additionally arranged on the basis of an existing open type cooling tower circulating water system, and a dry-wet combined cooling system is formed through integration of pipelines and valves. The system collects the temperature, flow, pressure, energy consumption and environmental parameters of each node in real time, and after data fusion and preprocessing, the cooling load and evaporation water consumption are calculated based on thermodynamic equilibrium and hydraulic equilibrium models. A multi-objective optimization model which takes minimization of evaporation water consumption as a main part and minimization of energy consumption as an auxiliary part is adopted, an artificial intelligence algorithm is used for real-time solving, optimal control parameters such as flow distribution, fan rotating speed and valve opening degree are output, and dynamic adjustment of the cooling system is achieved. The system continuously corrects and optimizes model parameters through a closed-loop feedback and self-learning mechanism, ensures that the water supply temperature reaches the standard, the evaporation water consumption is minimum and the energy consumption is optimal, and remarkably improves the water saving and operation efficiency of the industrial circulating water system.

The invention discloses a natural ventilation cooling tower and a dumbbell-shaped concrete filled steel tube cross strut thereof, the dumbbell-shaped concrete filled steel tube cross strut comprises four dumbbell-shaped steel tube limb columns and cross nodes, and the end parts of the dumbbell-shaped steel tube limb columns are connected with the cross nodes to form a cross structure; the cross joint comprises a vertical stiffening plate, an upper reinforcing ring, a lower reinforcing ring, a plurality of joint sleeves and a plurality of joint webs, the upper reinforcing ring and the lower reinforcing ring are perpendicularly crossed with the vertical stiffening plate, the joint webs are connected with the joint sleeves, and the joint sleeves, the joint webs, the upper reinforcing ring and the lower reinforcing ring form a dumbbell-shaped structure with the vertical stiffening plate as the central axis. Open holes are formed in the reinforcing rings and used for pouring and circulation of concrete, the four dumbbell-shaped steel pipe limb columns are arranged at the open holes of the upper reinforcing ring and the lower reinforcing ring, and a closed space is formed by the joint sleeve, the joint web, the upper reinforcing ring, the lower reinforcing ring and the four dumbbell-shaped steel pipe limb columns. The problem of material waste caused by rich in-plane directional bearing capacity of a circular section can be solved.

The embodiment of the application provides a gravity self-balancing uniform water distribution system, which comprises first, second and third stage gravity self-balancing water distribution pipelines. Each second stage gravity self-balancing water distribution pipeline is connected to the first stage gravity self-balancing water distribution pipeline, and each third stage gravity self-balancing water distribution pipeline is connected to the second stage gravity self-balancing water distribution pipeline. The circulating water of the cooling tower is automatically depressurized after entering the first stage gravity self-balancing water distribution pipeline, and flows into each second stage gravity self-balancing water distribution pipeline on the basis of the self-weight of the water to realize double uniform water distribution. The water level height of each second stage gravity self-balancing water distribution pipeline is consistent, and the water inlet flows to the third stage gravity self-balancing water distribution pipeline again. The pressure at each water nozzle directly or indirectly connected to the third stage gravity self-balancing water distribution pipeline is consistent, and the water outlet of each water nozzle and the spraying area are substantially the same, so that uniform water distribution is realized, the water inlet is not affected by the water pressure, and the cooling efficiency of the cooling tower is significantly improved.

The invention discloses a rotary kiln pyrolysis process preheating and replacing method which comprises the following steps: replacing and preheating an upgrading system when a rotary kiln is started, performing low-load operation on the rotary kiln, heating the rotary kiln by a rotary kiln hot blast stove and a flue gas fan, closing a pipeline valve from a dry gas fan to a first dust remover, and performing low-load operation on the rotary kiln; a rotary kiln nitrogen replacement valve is slightly opened, nitrogen enters the rotary kiln through a dry gas guide screw for replacement and heat removal, an oil and gas pipeline is preheated, direct cooling tower spraying cooling water and indirect cooling tower circulating cooling water are put into use, a coal gas fan is started for system circulation, and an electrical tar precipitator outlet is opened to a rotary kiln starting line valve; the invention further discloses a rotary kiln quality improvement system, the rotary kiln pyrolysis process preheating and replacement method is adopted, the start-up time is effectively shortened, the investment and operation cost is saved, and meanwhile a foundation is laid for long-period stable operation of the system.

The invention discloses a natural draft cooling tower and a lattice type concrete filled steel tube cross strut thereof, the lattice type concrete filled steel tube cross strut comprises four lattice columns and cross nodes, the end parts of the lattice columns are on the same plane and are connected with the cross nodes to form an X-shaped structure, and each lattice column comprises a concrete filled steel tube column limb and a web member for connecting the adjacent concrete filled steel tube column limbs; the cross joint comprises two joint branch assemblies and a joint belly assembly connected with the two joint branch assemblies, and each joint branch assembly comprises a joint panel, a first covering panel and a second covering panel, wherein the first covering panel and the second covering panel cover the joint panel. The joint face plate comprises a joint top plate, a joint bottom plate, a joint stiffening plate and a reinforcing ring plate, the joint stiffening plate and the reinforcing ring plate are arranged between the joint top plate and the joint bottom plate, and open holes are formed in the joint top plate, the joint bottom plate and the reinforcing ring plate and used for concrete pouring and circulation. And the four latticed columns are arranged at the holes of the node top plates and the node bottom plates of the two node branch assemblies. The use amount of strut steel and concrete is reduced, and the construction speed and the construction quality are improved.

The invention relates to a group control optimization method and system for a cold station system, and belongs to the technical field of automatic control, and the method comprises the steps: carrying out the minimum optimization of a first-stage group control optimization objective function through a mixed integer programming algorithm with the start-stop state of each device as an optimization variable during the operation of the cold station system, and obtaining a second-stage group control optimization objective function; the start-stop state of each device of the cold station system is controlled during first-stage group control; and on the basis of the first-stage group control, performing minimum optimization on the second-stage group control optimization objective function by taking chilled water outlet water temperature, chilled pump frequency, cooling pump frequency and cooling tower frequency as optimization variables through a model prediction control algorithm, and controlling the operation state of operation equipment when the cold station system is in the second-stage group control. Therefore, energy consumption is reduced as much as possible and energy efficiency is improved.

A cooling-tower performance testing device, comprising: a first barrier member (11) arranged on a water output pipeline of an RIS-RHR heat exchanger (21); a heat-source obtaining assembly (12), which has a first end mechanically connected between the first barrier member (11) and a water outlet of the RIS-RHR heat exchanger (21) and a second end mechanically connected to an EHR gate valve (31); and a second barrier member (13), which is arranged on a pipeline connected between a water outlet of a PTR heat exchanger (51) and a hot-side water inlet of an ECS heat exchanger (41). The device enables an ECS to obtain a stable heat source from one loop, and supplies heat to the ECS heat exchanger (41), and a heat source is thus provided for carrying out a cooling-tower performance test, without temporarily laying a large number of pipelines, thereby omitting a large amount of pipeline disassembly and site restoration work, and also effectively shortening a test duration and reducing test costs. Further provided is a cooling-tower performance testing method.

The utility model discloses a comprehensive treatment device of a circulating cooling water system. The comprehensive treatment device of the circulating cooling water system comprises a cooling circulating water pool, a water pump, a cooling tower, a first electromagnetic frequency mixing scale inhibition device, a side filtration system, an electrochemical water treatment device and a hypochlorous acid sterilization device, the water supply main pipe is matched with the heat exchange device and connected with the cooling tower through the water return main pipe, and the cooling tower is connected with the cooling circulation water pool. The first electromagnetic frequency mixing scale inhibition device is arranged on the water supply main pipe; the bypass filter system, the electrochemical water treatment device and the hypochlorous acid sterilization device are respectively connected with the water return main pipe and the cooling circulating water tank through pipelines. The utility model provides a comprehensive treatment device of a circulating cooling water system, which can ensure the heat exchange efficiency of the circulating cooling water system and realize long-term stable operation on the premise of ensuring that the water quality reaches the standard and greatly reducing chemical agents.

The invention relates to the technical field of thermal power generation, in particular to a closed circulation cold end optimization method, device and system, and the method comprises the following steps: obtaining the historical operation data of a unit from a power plant monitoring information system, the data comprises circulating water flow, circulating water inlet temperature, circulating water outlet temperature, condenser backpressure water pump motor current, generator power, medium and low pressure heat supply steam flow, condenser steam-water temperature and condenser water inlet and outlet pressure; s2, performing abnormal value processing on the data obtained in the step S1, namely screening out an abnormal value, and repairing and filling the abnormal value by using an interpolation method; based on the actual condition of the power plant, the unit load and the steam admission amount of the condenser are fitted through a large amount of historical data in the step S2; the total power for starting different numbers of circulating water pumps and fans and the water flow corresponding to the circulating water pumps are determined according to the historical data in the step S2; respectively establishing a condenser model and a cooling tower model; constructing a circulating cooling system model, coupling the condenser model and the cooling tower model, carrying out iterative calculation until convergence or reaching the maximum number of iterations, and obtaining the condenser outlet water temperature, the cooling tower outlet water temperature, the condenser back pressure, the vacuum degree and the power generation power; fitting a correction coefficient curve by referring to the technical specification of a power plant and combining the historical data in the step S2 with the condenser backpressure-generated power correction coefficient graph; and calculating the generated power and the net output power according to the unit load and the auxiliary machine consumption, and outputting an auxiliary machine configuration scheme corresponding to the maximum net power.

The invention discloses an efficient refrigerating machine room energy-saving automatic control system based on reinforcement learning, and the system comprises the following modules: an operation data collection module which is used for collecting key equipment operation parameters and generating unified time sequence data; the energy consumption modeling module constructs energy consumption mathematical models of the water chilling unit, a water pump and a cooling tower and stores the energy consumption mathematical models into a database; the cooling capacity prediction module is used for predicting the future cooling capacity demand based on the historical data and the environmental parameters; the feed-forward optimization module is used for optimizing power distribution by using an adaptive particle swarm algorithm and generating control parameters; the state correction module automatically adjusts the running state according to the running efficiency deviation condition; the cooling strategy optimization module introduces an improved DSAC algorithm to optimize a cooling control strategy; and the instruction deployment module deploys the strategy to an actual system and outputs a regulation and control instruction. The energy efficiency management level of the refrigerating machine room is improved, and integration of energy conservation and intelligent control is achieved.

The invention discloses a data center negative pressure two-phase liquid cooling distribution method and device, and relates to the technical field of data center liquid cooling. A server cold plate, an outdoor closed cooling tower and a data center two-phase cooling distribution unit CDU are connected through a closed circulating pipeline, so that a liquid cooling working medium is conveyed to the server cold plate through a liquid separator at an outlet of the CDU, absorbs heat of a server in a cold plate flow channel and is completely gasified, and the gasified cooling working medium is driven by a circulating pump through a heat insulation pneumatic pipeline to be conveyed to the server cold plate. A gaseous cooling working medium enters a primary side composite gas phase pipeline and is directly conveyed to a condensation section of a primary side outdoor closed type cooling tower, the condensation section adopts a finned tube bundle structure, the gaseous cooling working medium exchanges heat with air / spray water in the condensation section and is liquefied, and the liquefied cooling working medium enters a negative pressure heat exchanger unit in the CDU under the assistance of a circulating pump or gravity; a low-temperature gaseous cooling working medium after heat exchange enters a composite gas phase pipeline on the primary side under the action of a sucking pump and is mixed with a high-temperature gaseous cooling working medium coming out of a server cold plate, and then the precooled working medium forms a liquid working medium in a supercooled state through a throttling valve and is injected into a liquid pool at the bottom of a liquid storage tank; and redistributing to each server cold plate to finish cooling circulation.

The invention discloses a rinsing water treatment device for a glass fiber reinforced plastic cooling tower, and relates to the technical field of cooling tower rinsing water treatment devices.The rinsing water treatment device comprises a mounting frame, a cleaning mechanism is arranged on the outer side of the mounting frame, a self-checking mechanism is arranged on the outer side of the mounting frame, the cleaning mechanism comprises a cleaning unit, and the cleaning unit is arranged on the outer side of the mounting frame; the cleaning unit can effectively clean impurities accumulated in the equipment, the cleaning mechanism further comprises a processing unit, the processing unit is arranged on the outer side of the mounting frame and can carry out centralized processing on the impurities, the self-checking mechanism can carry out self-checking on the distance between baffles in the equipment, and the cleaning unit comprises two first stepping motors; according to the rinsing water treatment device for the glass fiber reinforced plastic cooling tower, the cleaning unit, the treatment unit and the self-checking mechanism are arranged, so that the problem that workers need to check the rinsing water treatment device regularly when the rinsing water treatment device is used can be effectively avoided.

The invention provides a performance optimization method and system for a closed cooling tower, and relates to the technical field of data processing.The method comprises the steps that input parameters describing the closed cooling tower are obtained; determining a cumulative distribution function of each input parameter; discretizing each input parameter to form a discretized simulation sample; performing computational fluid mechanics simulation on the closed cooling tower by utilizing the simulation samples, and determining system response of each simulation sample; performing principal component analysis on system response data through singular value decomposition; establishing an incidence relation between the input variable and the score matrix through Kriging interpolation, and forming a complete preliminary prediction model between the input variable and the system response; through a high-dimensional model representation technology, the high-order interaction effect of the preliminary prediction model is optimized, and a performance prediction model of the closed cooling tower is obtained; in order to improve the cooling efficiency and reduce the construction cost, the design parameters of the closed cooling tower are optimized through a butterfly optimization algorithm.

The invention provides a cooling tower system optimal operation parameter self-adaptive regulation and control method, which comprises the steps of collecting multi-source high-frequency data in a system operation process, and obtaining a standardized variable sequence through normalization, abnormal value processing and time sequence consistency verification. A sliding window mechanism and a lightweight causal discovery algorithm are combined, a causal atlas is dynamically constructed and fused, parameters are corrected in real time through an incremental Bayesian network, a dominant causal path is extracted, lightweight CMA-ES rolling optimization is executed in an equivalent control subspace after dimension reduction, optimal control parameters are solved, system closed-loop adjustment is driven, and the optimal control parameters are obtained. Meanwhile, a map confidence degree evaluation and depth reconstruction mechanism is set, dynamic self-adaption of a causal structure and parameters is ensured, the response capacity of a cooling tower system to working condition changes can be improved, and energy efficiency and operation stability are optimized.

The data center liquid cooling air conditioning system and the control method have the prospective intelligent regulation and control characteristic based on machine learning prediction and model prediction control, multi-dimensional operation data are obtained in real time through a data collection module, and the data are input into a thermal load prediction model after being preprocessed; and a thermal load sequence in a future time window is accurately predicted, optimal control parameters are calculated through an optimization algorithm, and the operation states of the cooling liquid circulating pump set and the outdoor cooling tower are dynamically adjusted. According to the system, the hysteresis problem of traditional feedback control is effectively solved, advanced response and accurate matching of thermal load changes of the data center are achieved, the temperature control stability and the overall energy efficiency of the system are remarkably improved, and meanwhile the adaptability of the system to load fluctuation and external environment changes is enhanced.