8330results about "Efficient regulation technologies" patented technology

The invention relates to the technical field of air conditioner energy-saving operation control, and discloses a central air conditioner energy-saving operation control method and system. The method comprises the following steps: acquiring and processing data through a temperature and humidity sensor to obtain a temperature and humidity distribution index; calculating load values according to the indexes and the personnel density to form a distribution diagram; regulating and controlling cold and heat source equipment according to the distribution map to obtain operation parameters; adjusting the water pump fan based on the parameters to form balance data; adjusting the end equipment according to the data to generate a control instruction; and the system state is adjusted in real time according to instructions and comfort feedback to realize energy-saving operation. The problem of energy waste caused by decentralized control of subsystems of a traditional central air conditioning system is solved. By constructing a complete closed-loop control system from environmental perception, load prediction to equipment regulation and control, the operation efficiency of the system under partial load conditions is improved. And meanwhile, refined control is achieved according to different requirements of different areas, and energy consumption is reduced to the maximum extent on the premise that the comfort level of the user is guaranteed.

The invention relates to the technical field of environment perception, and discloses an optimization method and device for a multi-climate self-adaptive environment perception cooling fan system, and the method comprises the steps: collecting multi-point temperature, humidity and air pressure data, and carrying out the filtering processing, and obtaining an environment state vector; executing mathematical modeling of the multi-degree-of-freedom cooling system according to the environment state vector to obtain a linearized state space model; performing temperature gradient estimation and humidity compensation based on the linearized state space model to obtain an adaptive control law; inputting the adaptive control law into a model-free adaptive prediction controller to obtain a rolling optimization control sequence; weight self-adaptive adjustment and heat dissipation efficiency hierarchical prediction control are carried out on the rolling optimization control sequence based on climate conditions, fan rotating speed control and wind direction adjustment execution signals are generated, the problem that a traditional heat dissipation system is not sensitive to space temperature distribution and humidity changes is solved, and the heat dissipation control precision under different humidity conditions is improved.

The invention provides a subway station central air conditioner full-link energy-saving system and method based on wind balance. Belongs to the technical field of air-conditioning energy conservation. The method comprises the steps that environmental data inside and outside a subway station are collected in real time through a sensor network, and the collected environmental data are uploaded to a central air conditioner full-link energy-saving control platform; the central air conditioner full-link energy-saving control platform dynamically adjusts the air volume of the air supply pipe and the air return pipe through fan control according to the collected data; by collecting environment data in real time and combining an advanced control algorithm, the system can dynamically adjust the rotating speed of a fan, the load of a refrigerating unit, the ratio of fresh air to return air and the like, so that the running state of the air conditioning system is optimized, energy consumption is effectively reduced, and the overall energy-saving effect of the system is improved.

The invention discloses an air conditioning system and a control method thereof. The air conditioning system comprises an air conditioning outdoor unit; the air conditioning outdoor unit comprises a compressor, an outdoor heat exchanger and an outdoor fan; the outdoor fan is at least provided with a first working mode and a second working mode; and when the outdoor fan runs in the first working mode, a wind gear is higher than that when the outdoor fan runs in the second working mode. The control method comprises the following steps that S1, the air conditioning system is controlled to enter arefrigeration mode; S2, according to the outdoor environment temperature and / or preset hours, the outdoor fan is controlled to enter the first working mode or the second working mode. According to the control method of the air conditioning system, the air conditioning system can control the outdoor fan to enter the first working mode or the second working mode according to the outdoor environmenttemperature and / or the preset hours, and when the outdoor fan runs in the second working mode, the wind gear of the outdoor fan is lowered, so that the use reliability the air conditioning system cannot be affected, and the requirement of a user on comfortableness can be met.

The invention relates to the technical field of mine ventilation control, in particular to a mine fan ventilation control method and system based on digital twinning. The method comprises the following steps: carrying out data preprocessing on acquired mine monitoring data; performing feature extraction on the preprocessed mine monitoring data; utilizing a random forest algorithm to predict the relationship between the data characteristics and the fan air volume; a digital twinborn model is used for resolving the relation between the data characteristics and the fan air volume, and a fan ventilation control strategy is obtained; and generating a PLC control instruction based on the fan ventilation control strategy. And through multi-source data fusion and deep analysis, the real-time ventilation requirement of the mine can be accurately grasped. Based on random forest algorithm prediction and digital twinborn model calculation, dynamic and accurate adjustment of the air volume of the draught fan is achieved, it is ensured that the concentration of harmful gas in all underground areas is maintained within a safety threshold value, the oxygen content is sufficient, an ideal environment is created for personnel operation and equipment operation, and the safety and reliability of a ventilation system are remarkably improved.

A remote test apparatus is configured to simulate an environment of at least one remotely located room and configured to receive at least one air sample from the at least one remotely located room. The apparatus includes a sealed enclosure forming an interior cavity and including an inlet in connection with the at least one remotely located room and an outlet in connection with a sample collection unit. The sample collection unit is configured to communicate the at least one air sample from the remotely located room at a first flow rate. The apparatus further includes at least one sensor disposed in the interior cavity and at least one air transfer unit configured to transfer test air from the interior cavity of the sealed enclosure to the at least one sensor at a second flow rate.

Techniques for operating an environmental sensing system are described. In an example, a cloud-based server system receives a first indication that a first type of air pollutant is present within a first structure from a first plurality of indoor air quality (IAQ) sensing devices positioned within the first structure. A second structure within a predefined distance to the first structure is then identified by the server system. The server system then determines that the first type of air pollutant is not present within the second structure. The server system then causes a second plurality of IAQ sensing devices positioned within the second structure to change an operating mode from a normal sensitivity mode to a high-sensitivity mode.

The invention relates to the technical field of clean environment control, in particular to a dynamic pipe network and model predictive control clean room energy-saving pressure control method and system. Obtaining current pipe network impedance according to the pipe network impedance curve; calculating the current valve impedance according to the valve opening; calculating the total pressure drop of the current pipe network; constructing a fan dynamic model based on a fan similarity law to calculate the air volume at the next moment; a clean room pressure difference dynamic model is constructed, and the clean room pressure difference at the next moment is calculated; constructing a state space model and a target function of a model prediction controller; and when the pressure difference of the clean room is unstable, predicting the change trend of the pressure difference of the clean room in the next time period, and reversely solving the optimal fan frequency and valve opening of the discretization state space model by using the model prediction controller so as to achieve the lowest pipe network impedance and obtain the optimal fan frequency. The control precision and robustness of the pressure difference of the clean room are remarkably improved, and meanwhile energy consumption is reduced.

An IAQ sensor module includes: a sensor configured to measure an amount of an item in air, the item being one of particulate matter, volatile organic compounds, and carbon dioxide; a minimum module configured to selectively store the amount of the item as a minimum value of the amount when a mitigation device has been on for at least a predetermined period, the mitigation device being configured to decrease the amount of the item in the air when on; a storing module configured to selectively store the minimum value as an initial minimum value; an offset module configured to determine a drift offset for the sensor based on a difference between the minimum value and the initial minimum value; and an adjustment module configured to determine an adjusted amount of the item in the air at the IAQ sensor module based on the amount and the drift offset.

The invention discloses an efficient refrigerating machine room air conditioner energy-saving intelligent control system and method, and relates to the field of air conditioner intelligent control. The method comprises the steps that air conditioner operation parameters, machine room equipment operation data and machine room environment data are collected and preprocessed; building a deep neural network by using a deep Q-learning reinforcement learning algorithm to obtain a thermal load demand of the machine room; introducing a nonlinear dynamic compensation function to calculate an air-conditioner dynamic energy efficiency coefficient and air-conditioner refrigeration power, and calculating the rotating speed of an air-conditioner compressor by referring to air-conditioner operation parameters; a PID (Proportion Integration Differentiation) controller is used for carrying out primary frequency conversion on a machine room air conditioner, and a multi-stage adjusting mechanism is used for correcting a primary frequency conversion result in real time according to machine room equipment operation data, machine room environment data change and frequency conversion conditions. According to the air conditioner energy-saving control method, efficient air conditioner energy-saving control is achieved by combining the deep Q-learning reinforcement learning algorithm, the nonlinear dynamic compensation function and the PID controller.

The invention discloses an airport terminal fresh air energy-saving optimization control method based on passenger space-time distribution prediction, and relates to the technical field of intelligent energy saving, and the method comprises the following steps: S100, collecting the real-time position and moving speed of a passenger, constructing a passenger space-time distribution change model, and forming a prediction basis of air pressure dynamic adjustment; and S200, based on the passenger space-time distribution change model, calculating air pressure gradient distribution of each functional area of the terminal, identifying local positive pressure and adjacent negative pressure areas, establishing a micro pressure difference grading early warning index, and determining a ventilation adjustment demand. By dynamically predicting passenger distribution, adjusting air supply and static pressure in real time and combining pressure difference early warning, airflow monitoring and countercurrent sealing control, airflow order is ensured, pollution gas is prevented from flowing backwards, and air quality and comfort are guaranteed. Based on a control model and an energy-saving strategy library of full-process data training, intelligent self-adaptive adjustment of the fresh air system is achieved, ventilation safety and energy efficiency are improved, and terminal service experience and operation efficiency are optimized.

The invention relates to the technical field of air-cooled air conditioner control, in particular to an air-cooled air conditioner control method and system based on deep learning, and the method comprises the following steps: obtaining sensor readings of indoor temperature, outdoor temperature and humidity and Wi-Fi channel state information, judging the position number and the activity state of personnel, calculating the position distribution of the personnel in combination with a time window, and calculating the position distribution of the personnel. And integrating to obtain a multi-dimensional environment and load state vector. According to the method, indoor and outdoor temperature, humidity, Wi-Fi channel state information and personnel position distribution and activity states are integrated through a multi-dimensional environment and load state vector, the personnel density change trend is dynamically calculated through a time window, the comprehensiveness and real-time performance of environment perception are enhanced, and high-dimensional data support is provided for control decision making. And a basic comfort degree deviation index is constructed based on the temperature deviation value and the humidity deviation value, and a multi-target performance index set is generated in combination with the wind speed value, the compressor start-stop frequency and the energy consumption power.

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 the technical field of intelligent control, in particular to an intelligent radiation constant-temperature and constant-temperature system and a remote monitoring method, and the system comprises a radiation tail end control module, a hydraulic balance adjusting module, a fresh air humidity regulation and control module, a cold and heat source matching module and a noise and vibration suppression module. According to the method, through fine collection and analysis of temperature data of differentiated areas and optimization of a heat exchange strategy, precise temperature control is achieved, the response capacity is improved, the fluid flowing state is dynamically adjusted, hydraulic balance is optimized, reasonable distribution of cold water and hot water is ensured, heat loss is reduced, energy efficiency is improved, and air quality monitoring and the humidity change trend are combined; the dehumidification and humidification capacity of the fresh air system is optimized, the humidity adjusting precision is improved, cold and heat source output is dynamically matched with environment heat loads, energy consumption optimization is achieved, hydraulic control and vibration suppression are optimized based on flow speed and vibration monitoring, the mute effect and comfort are improved, multi-dimensional data collaboration is achieved, and accurate adjustment, independent control and efficient energy consumption management are achieved.

The invention relates to the technical field of ward air purification systems, and discloses a ward air purification system which comprises an environment sensing module, a purification path planning module, a filter unit configuration module, a purification execution module, a dynamic adjustment module, a state monitoring module and a feedback control module. The environment sensing module obtains ward space information to construct an air flow topology; the purification path planning module calls air quality data to label the topology; the filter unit configuration module sets purification nodes and adjustment intervals; the purification execution module implements basic purification; the state monitoring module analyzes data to determine operation state characteristics, and the feedback control module generates monitoring records and performs visual feedback. The system can accurately perceive the air quality of the ward, scientifically plan the purification path, dynamically adjust the purification strategy, effectively improve the air quality of the ward and guarantee the health of patients and medical staff, and has high practical value.

The invention discloses an energy regulation and control method for a digital intelligent low-carbon building, and relates to the technical field of energy intelligent control, and the method comprises the following steps: constructing a multi-source feed-forward sensing link, unifying data collection timestamps, fusing people counting data, access control record data and wireless local area network probe data, and obtaining a multi-source feedback sensing link; passenger flow step fingerprints capable of reflecting instantaneous passenger flow change characteristics are generated and used for feedforward input of follow-up dynamic response; and performing crowded wave dynamic tracking based on passenger flow step fingerprints, analyzing a crowd movement track in combination with feedforward input, positioning a high-concentration air quality risk area, outputting a risk arrival time and intensity curve, and generating a feedforward ventilation time history input prediction link. According to the method, people flow changes are sensed and predicted through multi-source feedforward, a ventilation strategy is actively deployed, self-optimization is achieved in combination with feedback correction and closed-loop evaluation, and energy consumption is reduced and the service life of equipment is prolonged while air health and safety are guaranteed.

The invention discloses a secondary network heat supply temperature control method and device based on a negative pressure water mixing technology, and relates to the technical field of secondary network heat supply control. The secondary network heat supply temperature control method and device based on the negative pressure water mixing technology comprises the steps that S1, operation data, structure steady state data and thermal environment data in a current heat supply task are collected, and a standardized heat supply working condition data set is constructed after preprocessing; s2, local hydraulic fluctuation characteristics are evaluated, and the water mixing proportion, the water supplementing flow and bypass path configuration are dynamically adjusted; s3, jointly analyzing the temperature difference of supply water and return water, the heat deviation and the valve state, and driving water mixing adjustment and path optimization; s4, evaluating adjustment intensity and heat response deviation, and realizing abnormal disturbance response and adjustment strategy correction; and S5, recording negative pressure, uneven heat and cold and response data for subsequent diagnosis and steady state identification. The problems that a traditional water mixing control means is difficult to effectively inhibit pressure fluctuation of the water return end, local negative pressure is easily formed, and local energy waste and uneven heat distribution are caused are solved.

The invention relates to the technical field of intelligent control, and particularly discloses a clean environment control system for a clean cold operation room. Air particulate matter concentration in the operation room and pressure data before and after an HEPA filter are collected in real time; performing time sequence modeling on the air particulate matter concentration data and the pressure drop data before and after the filter by using a time sequence analysis technology based on deep learning to capture the change of a clean environment in an operation room and the change of a load state of the filter, and further performing time sequence correlation response analysis on the air particulate matter concentration and the pressure drop of the filter; and a potential correlation mode between the air cleanliness in the operation room and the working state of the filter is excavated, so that the air volume of the air feeder is dynamically adjusted. In this way, self-adaptive control over the cleanliness of air in the clean operation room can be achieved, meanwhile, the use efficiency of the HEPA filter is optimized, and unnecessary energy consumption and the replacement frequency of the filter are reduced.

The invention relates to the technical field of refrigeration equipment control, in particular to an air conditioner control method and system. Firstly, a refrigerant flow prediction model is established by combining the advantages of LSTM and XGBoost, a time sequence and static characteristics are accurately captured, prediction precision and system adaptability are improved, reliable data support is provided for intelligent regulation and control, refrigerant distribution is optimized, energy efficiency is improved, and energy consumption is reduced; secondly, the opening degree of an electronic expansion valve and the frequency of a compressor are controlled in a feedforward mode through a multivariable cooperative control algorithm, the load and the flow are accurately matched, the system efficiency is improved, it is ensured that all assemblies operate in a coordinated mode, energy waste is reduced, and stability and comfort are optimized; finally, PID feedback control is combined, the frequencies of the electronic expansion valve and the compressor are finely adjusted in real time, the optimal energy efficiency and stability of the system are ensured, closed-loop control is achieved, the temperature control precision is further improved, fluctuation is reduced, and the energy efficiency is optimized.

The invention discloses an outdoor workstation air quality monitoring and intelligent ventilation system and method, and belongs to the technical field of environment monitoring and intelligent ventilation control. The system is composed of an environment sensing module, an intelligent control unit and a ventilation execution device. And the environment sensing module realizes pollutant concentration field reconstruction through a multi-dimensional data fusion algorithm. The intelligent control unit constructs a dynamic ventilation model based on an improved fuzzy PID algorithm, and generates an optimal ventilation strategy in combination with meteorological prediction data and workstation structure parameters. And the ventilation execution device adopts a modular design to realize directional air supply and pollutant blocking. The method comprises four steps of real-time environment data acquisition, dynamic risk assessment, ventilation parameter optimization and execution mechanism linkage control, and remote intelligent regulation and control are realized through cooperation of edge computing and a cloud platform. According to the scheme, a passive response mode of a traditional ventilation system is broken through, and the technical advantages of accurate pollutant tracing, dynamic optimization of ventilation efficiency and intelligent adjustment of equipment energy consumption are achieved.

The invention relates to the field of coal mine exhaust control, in particular to a coal mine exhaust control method and device based on environmental perception. The method comprises the following steps: acquiring multi-dimensional monitoring signals based on environment sensing sensors at multiple positions of a mine, performing distributed sensing marking, and constructing a global gas concentration sensing graph; the method comprises the following steps: acquiring position information of operating personnel in real time based on a miner positioning sensor, performing short-time movement prediction on the operating personnel, and generating a miner movement prediction path; obtaining a coal mine internal structure chart, and carrying out average oxygen consumption rate budget and instantaneous oxygen supply demand calculation based on the miner movement prediction path to obtain oxygen supply demand indexes of each unit; and according to the oxygen supply demand index of each unit, intelligent exhaust power calculation adjustment is carried out, and a conventional exhaust control strategy is constructed. Ventilation efficiency of the coal mine area is improved, emergency blast treatment is carried out under the risk condition, the risk problem response capacity is greatly improved, and safety of the coal mine area is enhanced.

The invention relates to the technical field of air purification system control, and provides an air purification control method, device and equipment based on user information and a medium, and the method comprises the steps that user information and indoor environment information corresponding to the environment where a target air purifier is located are obtained; analyzing the user information, determining a user category and a health category, analyzing the indoor environment information, and determining a main pollutant type and pollutant concentration; predicting the purification mode of the target air purifier according to the user type, the health type, the main pollutant type and the pollutant concentration to obtain a target purification mode; and according to the target purification mode, the working state of the target air purifier is adjusted. According to the method, the user type, the health type, the main pollutant type and the concentration are comprehensively analyzed, the purification mode most suitable for the current environment is predicted, it is ensured that the purification mode always meets the requirements of the current environment and the user, invalid or excessive purification in a fixed mode is avoided, and the air purification efficiency is improved.

A method and system for controlling a heating, ventilation, and air conditioning system (HVAC) in a building based on adaptive model predictive control (MPC) is disclosed, and belongs to the technical field of intelligent building adaptive control. The method may include: acquiring operation data of the HVAC under different working conditions, and performing preprocessing on the acquired data; calculating a marginal fitness measure (MAD) of each data point for each class based on the preprocessed data, and calculating a fitness measure of each data point for each class by combining MADs of all descriptors to obtain a global fitness measure (GAD); setting a GAD threshold, and classifying current operation states of the system according to classification rules; and adopting adaptive control strategies for different operation states since model parameters of each class are fixed after classification.

The invention discloses a multi-mode intelligent detection ventilation cabinet variable air volume system based on AI, and particularly relates to the field of intelligent detection control, which comprises a multi-sensor module, a task detection calculation processing module and a variable air volume intelligent control module, according to the invention, data of visible light-infrared-ultraviolet three spectrums and the like are collected through multiple sensors, and fire early warning, smoke detection and collision risk assessment are carried out according to the data; the fire identification unit judges the fire according to different wave band characteristics and threshold values; the smoke detection unit calculates smoke related parameters by using a plurality of algorithms and gives an alarm in a grading manner; the fume hood window obstacle detection unit judges the risk level and controls a front window by using a binocular camera to measure depth and other information; the variable air volume intelligent control module adjusts the air volume according to the detection result, the personnel state recognition algorithm distinguishes the personnel state to switch the operation mode, the dynamic air volume control algorithm adjusts the air volume according to the area proportion of the operation area, and the off-post grading alarm mechanism guarantees the experiment safety.

The invention relates to the field of air conditioner control, and provides a variable frequency air conditioner outdoor alternating current motor overvoltage control method and system.The control method comprises the steps that the temperature of a compressor, axial temperature distribution data of an outer coil pipe, the temperature of an outer fan and current opening parameters of an electronic expansion valve are obtained in real time; when it is detected that the power supply voltage exceeds a preset threshold value, a compressor frequency correction coefficient is dynamically generated based on gradient change characteristics of axial temperature distribution data of the outer coil pipe, and meanwhile the following sub-steps are executed: according to the difference value of the compressor temperature and the outer fan temperature, the compressor frequency correction coefficient is combined; executing first frequency reduction operation to reduce the operation frequency of the compressor, and adjusting the opening degree of the electronic expansion valve; based on the concentration ratio of the high-temperature area of the outer coil pipe, an outer fan is controlled to be switched in a multi-stage rotating speed mode; and when it is detected that the temperature rise rate of the highest temperature point of the inner coil pipe and the outer coil pipe exceeds the critical value in two continuous periods, linkage adjustment of second frequency reduction operation and electronic expansion valve opening compensation is triggered.

The invention relates to the technical field of air conditioners, particularly provides an air conditioner control method and an air conditioner, and aims to solve the problem that in the prior art, when the indoor environment temperature of an air conditioner is close to the set temperature, the indoor environment temperature cannot be accurately controlled. In order to achieve the purpose, the control method of the air conditioner comprises the steps that an indoor environment temperature value is obtained at intervals of a set duration value; determining a first temperature difference value according to the operation mode of the air conditioner, the set temperature value and the indoor environment temperature value; according to the operation mode, the current indoor environment temperature value and the last indoor environment temperature value, a second temperature difference value is determined; and based on the first temperature difference value and the second temperature difference value, the numerical value of at least one of the compressor frequency, the outdoor fan rotating speed and the indoor fan rotating speed is adjusted. The first temperature difference value and the second temperature difference value are comprehensively considered, the frequency of the compressor, the rotating speed of the outdoor fan and the rotating speed of the indoor fan are adjusted, the temperature control accuracy is improved, meanwhile, repeated temperature change is avoided, and energy consumption is reduced.

Provided in the present invention are an abnormal-sound detection method and system based on diffusion denoising for an air conditioner outdoor unit. The method comprises: acquiring normal operation sound data of an air conditioner outdoor unit and interference sound data in an environment where air conditioner detection is performed; pre-processing the sound data to obtain respective time-frequency features; training a Gaussian mixture model on the basis of the time-frequency feature of the interference sound data, obtaining the data distribution thereof to perform random sampling, and superimposing, onto the time-frequency feature of normal sound data of an air conditioner, sound data sampled from the data distribution, so as to obtain fifth sound data and a corresponding sampling step label; training a neural network model by means of the normal operation sound data of the air conditioner outdoor unit and the fifth sound data, so as to obtain a trained anti-interference abnormal-sound detection model for an air conditioner outdoor unit; and acquiring operation sound data to be subjected to detection of the air conditioner, pre-processing same, and then inputting same into the trained abnormal-sound detection model for an air conditioner, so as to determine whether an operation sound of the air conditioner is abnormal. The present application improves the anti-interference performance of a detection algorithm and the air conditioner outdoor unit detection efficiency, thereby reducing the labor cost.

The invention relates to the technical field of intelligent building environment control and energy management, and provides a building ventilation regulation and control method and equipment based on multi-target space-time analysis in order to solve the problems of high energy consumption, uncontrollable infection risk and response lag in the prior art. Original data and the spatial-temporal features are combined into a multi-modal fusion data set, an air quality change rule is learned based on an LSTM model, a future air quality state matrix is output, a multi-target dynamic optimization function is constructed, an optimal regulation and control strategy of a fan, fresh air and purification equipment is generated, and the optimal regulation and control strategy of the fan, the fresh air and the purification equipment is obtained. The response speed is improved while energy consumption is reduced and infection risks are controlled, and the system is particularly suitable for public places such as hospitals, schools and nursing homes with high requirements for indoor gas environments.