4823 results about "Indoor air" patented technology

The invention relates to a multi-dimensional air purification method and system based on AI intelligent big data deep analysis, and solves the problem that it is difficult for an air purifier to achieve uniform and efficient purification of the whole indoor space. According to the coordinates and the areas of the sub-regions contained in the target region cluster, the mass center position of the target region cluster is obtained through calculation and serves as the target position of the air purifier; a path planning algorithm is used for planning a moving path from the current position to the target position for the air purifier, and the air purifier is controlled to move according to the moving path; and the size, the pollutant concentration and the type of the polluted area of the area cluster are obtained and input into a preset air purifier purification parameter adjustment model, air purifier purification parameters are output, and purification parameter adjustment is conducted according to the air purifier purification parameters after the air purifier moves to the target position. The indoor air purification device has the following effect that the indoor air purification efficiency and quality are improved.

The omitted right view is a mirror image of the left view; the broken lines shown in the reproductions depict portions of the indoor air conditioning control unit and form no part of the claimed design.

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.

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 relates to the technical field of energy consumption management, and particularly discloses an AI-based clean room dynamic energy consumption management system and method. According to the method, a deep learning algorithm is introduced to carry out deep interaction analysis on clean room indoor air quality parameter time sequence data and environment change driving event data such as the number of indoor personnel, the external environment temperature, the room door opening and closing state and the equipment power, so that intelligent reasoning of the dynamic evolution process of the clean room indoor air quality is realized; according to the method, the air quality parameter prediction result is compared with the preset air quality standard range so as to predict the air quality change in the future short time under the current driving event, and then the short-time air quality parameter prediction result is compared with the preset air quality standard range so as to carry out feedforward adjustment on the HVAC system operation parameters of the clean room according to the difference between the short-time air quality parameter prediction result and the preset air quality standard range. According to the method, environmental changes can be actively predicted, smooth pre-adjustment is conducted in advance, the air quality in the clean room is kept within the preset standard range, meanwhile, unnecessary energy waste is remarkably reduced, and the environmental stability is improved.

The invention relates to an energy-saving enthalpy difference test room, which comprises two adjacent rooms, namely an indoor environment simulation room and an outdoor environment simulation room, and further comprises an indoor air handling unit, an outdoor air handling unit and an indoor and outdoor air exchange unit, the outdoor environment simulation chamber is used for placing an outdoor unit of an air conditioner to be tested, the indoor air processing unit is installed in the indoor environment simulation chamber and can adjust the temperature of the indoor environment simulation chamber, and the outdoor air processing unit is installed in the outdoor environment simulation chamber and can adjust the temperature of the outdoor environment simulation chamber. The indoor and outdoor air exchange unit is communicated with the indoor environment simulation chamber and the outdoor environment simulation chamber, and cold / hot air generated by the indoor unit of the tested machine can be introduced into the outdoor environment simulation chamber.

The invention discloses an indoor air quality monitoring method and system based on multi-dimensional analysis, and belongs to the technical field of air quality monitoring. The indoor air quality monitoring method based on multi-dimensional analysis comprises the steps that various data of a chemical sensor, an optical sensor and an acoustic sensor are collected; preprocessing the data, including unifying sampling frequency and normalizing different data formats; performing multi-dimensional feature extraction to obtain a multi-modal feature; carrying out feature fusion by adopting a machine learning algorithm; the air quality state is evaluated based on the fusion features; through multi-source data fusion analysis, the problems of one-sided monitoring result and insufficient reliability of a single sensor are solved, the monitoring accuracy and reliability are improved, and the method can be widely applied to scenes such as smart homes and office buildings.

The present disclosure provides a carbon dioxide absorption composition, which includes a solution of an amino compound in a solvent comprising water and a glycol, as well as a method of using such composition to capture CO2. The present composition can be particularly advantageous for indoor use, with additional benefit for managing total volatile organic compounds and humidity to enhance overall indoor air quality.

The invention relates to an air purification method and system fused with AI intelligent big data analysis, and solves the problem that the purification effect is greatly reduced due to the fact that an air purifier cannot adjust operation parameters in time according to upcoming air quality changes in the operation process. The method comprises the following steps: inputting real-time gas related data and gas related data in a historical past time range into a pre-trained air quality prediction model, and outputting an air quality prediction result in a future preset time range; and the mode set by the user about the air purifier and the air quality prediction result in the future preset time range are input into the air purifier operation parameter optimization model, the optimized air purifier operation parameters are output, and the air purifier is indicated to perform corresponding operation according to the optimized air purifier operation parameters. The intelligent air purifier has the following effects that precise and intelligent air purification is achieved, the indoor air quality is effectively improved, and various requirements are met.

The invention relates to the technical field of indoor air quality monitoring, and discloses an indoor air quality joint detection system fused with a space-time diagram neural network. The system comprises a multi-source sensor data acquisition module for acquiring multi-source air quality data flow by configuring various sensors; the space-time diagram construction module constructs space-time diagram data according to the spatial position and the time sequence of the sensor; the fusion processing module adopts a space-time diagram neural network to perform feature fusion on the space-time diagram data to generate an air quality fusion feature set; the prediction strategy module determines a prediction strategy based on the remaining duration of the current time and the end time of the prediction period, and performs air quality prediction in combination with the fusion feature set; the dynamic adjustment module analyzes the real-time change of the data, constructs the pollution change degree and tendency degree, and adjusts the detection control parameters according to the pollution change degree and tendency degree; and the joint detection output module synthesizes the prediction result and the adjustment parameters to generate an indoor air quality joint detection report. The system provides powerful support for indoor air quality evaluation.

The invention relates to the technical field of indoor air conditioning, and particularly discloses an intelligent management system for indoor air conditioning, and the system comprises a collection module which collects indoor environment data based on Internet of Things equipment, extracts target features from the environment data through a deep learning algorithm, and builds an operation parameter generation model according to the target features; the control module is used for acquiring the target characteristics in real time, inputting the target characteristics into an operation parameter generation model, and adjusting the operation parameters of the air conditioner according to the output of the operation parameter generation model; and the optimization module is used for sorting the target time points according to the time axis sequence, obtaining the total energy consumption of the single air conditioner between the two adjacent target time points, analyzing the change trend of the total energy consumption by utilizing a machine learning algorithm, and optimizing the operation parameters of the air conditioner. According to the invention, depth perception, single-machine adaptive control and multi-machine collaborative optimization are fused, and real-time energy consumption monitoring and carbon emission optimization are realized.

The invention discloses a building integrated energy system optimization scheduling method giving consideration to the comfort level of a light storage soft environment, and relates to the field of building energy system optimization scheduling, and the method comprises the steps: building a photovoltaic output uncertainty model based on Beta distribution according to typical daily solar radiation intensity data; secondly, constructing an energy storage model; thirdly, a comfort level quantitative model considering temperature regulation and control of the indoor air conditioner and the electric water heater is constructed, and the influence on the environmental comfort level is reflected laterally; and finally, according to the various formed models, constructing a building integrated energy system optimization scheduling model considering the light storage soft comfort degree, and performing solving based on a mixed integer linear programming method. The environment comfort level of the building integrated energy system can be quantified, the flexibility of the building integrated energy system is improved by introducing photovoltaic and energy storage equipment, flexible scheduling of load resources is facilitated, peak load shifting is better achieved, the operation cost of the building integrated energy system is reduced, and the operation efficiency of the building integrated energy system is improved.

The invention discloses an air conditioner efficiency test system and a control method of an air conditioner efficiency test platform. The method comprises the following steps: dynamically adjusting the air dry bulb / wet bulb temperature of a test room of an existing test bed based on a dynamic temperature control adjusting technology; acquiring a real-time building thermal load of the test room through a building thermal load prediction simulator; the dynamic change of the air dry-bulb temperature of the test room is calculated in real time through the indoor air dry-bulb temperature prediction simulator; and the dynamic change of the air wet bulb temperature of the test room is calculated in real time through the indoor air wet bulb temperature prediction simulator. According to the invention, the problem that the dynamic operation energy efficiency and performance parameters of the tested air conditioner cannot be obtained through the enthalpy difference method test bench because the existing enthalpy difference method test bench cannot control the dynamic change process of the building thermal load of the test room along with the refrigeration / heating capability of the tested air conditioner in the prior art is solved; and the actual operation performance level of the air conditioner cannot be reflected.

This preferred embodiment pertains to a system designed to manage and optimize indoor air quality within a certain space. It employs a processor, multiple sensors, air dampers, and highly sophisticated machine learning code to control air flow, consider energy consumption, and analyze air quality data to maintain optimal conditions for both health and energy efficiency.

The invention discloses a BIM-based indoor energy-saving design method and system for a building. The method comprises the following steps: S1, building information modeling is utilized to construct an indoor building information modeling data model of the building; s2, generating a simulation input data set of computational fluid dynamics; s3, obtaining an indoor airflow flow state distribution result of the building; s4, analyzing an indoor airflow flow state distribution result of the building, and generating an optimization target data set; s5, based on the optimization target data set, an indoor air flow optimization algorithm is adopted to optimize indoor ventilation system parameters, windowing configuration and indoor layout of the building, and candidate indoor air flow optimization schemes are generated; and S6, verifying the candidate indoor airflow optimization scheme by using a computational fluid dynamics simulation engine, and determining an optimal building indoor airflow energy-saving design scheme by comparing the flow state distribution results of the building indoor airflow before and after optimization. According to the air flow characteristics of different indoor areas of the building, the optimal turbulence calculation model is adaptively selected to carry out indoor energy-saving design of the building.

The present invention discloses a floor radiation cooling system and an anti-condensation control method, which relate to the technical field of radiation air conditioning. The method comprises: real-time collection of indoor temperature and humidity, electric three-way valve opening, water pump flow and fresh air unit parameters; using particle swarm algorithm (PSO) to optimize radial basis function neural network (RBF) weights and construct a PSO-RBF prediction model; inputting indoor air temperature, relative humidity, fresh air speed, fresh air humidity, valve opening and water pump flow into the model, outputting surface temperature and calculating condensation risk value with current dew point temperature, dynamically regulating fresh air speed and humidity to achieve anti-condensation; and adjusting the radiation surface temperature based on the PMV thermal comfort model to maintain thermal comfort. The method uses a dual control mechanism to ensure that the radiation surface is prevented from condensation while using the radiation surface to independently bear the sensible heat load, effectively avoiding mold growth and maintaining a stable indoor thermal environment.

The invention relates to an intelligent multi-dimensional air purification cloud intelligent control method and system, and solves the problem that the complexity of an indoor environment, such as temperature and humidity, concentration of other pollutants and factors of different sensitivities of a user to air quality, cannot be comprehensively considered due to the fact that operation of a purifier is adjusted simply according to a single air quality index. The method comprises the following steps: analyzing a voice control instruction to extract key information, analyzing the extracted key information, real-time air quality data and air quality trend information in a future preset time range, inputting the information into an intelligent decision algorithm model of a cloud end, and outputting operating parameters needing to be adjusted of the air purifier, forming a parameter adjustment decision instruction; the formed parameter adjustment decision instruction is issued to an air purifier terminal through a network; and the air purifier responds to the parameter adjustment decision instruction to adjust the operation parameters of the air purifier. The method has the following effects that the air quality is improved, and the requirement of a user for the indoor air environment is met.

The invention discloses an environment-friendly cementing material capable of efficiently adsorbing formaldehyde and a preparation method of the environment-friendly cementing material, and relates to the technical field of formaldehyde adsorption materials, and the environment-friendly cementing material is prepared from the following raw materials in parts by weight: 30-50 parts of activated carbon powder, 10-20 parts of diatomite powder, 8-10 parts of metal organic framework powder, 12-18 parts of a natural gelatinizing agent, 1-2 parts of a plasticizer and 2-4 parts of nano titanium dioxide. The activated carbon powder has an extremely high specific surface area and can effectively adsorb formaldehyde molecules in air. The porous structure of the diatomite powder increases the adsorption capacity of the material, and improves the formaldehyde removal efficiency. The metal organic framework powder has a unique pore structure and chemical properties, and can specifically adsorb formaldehyde and other volatile organic compounds (VOCs). The environment-friendly cementing material has the advantages of being efficient in formaldehyde adsorption, environment-friendly, durable, multifunctional, easy to process, economical, practical and the like, and is an ideal indoor air purification material.

The utility model provides a cyclically-operated carbon dioxide trapping device. A shell of the cyclically-operated carbon dioxide trapping device is connected with an air inlet pipeline, an air outlet pipeline and an exhaust pipeline; the shell is internally provided with a reaction box body, the reaction box body is provided with two reaction cabins, and each reaction cabin is internally provided with a fan, a heater and a carbon dioxide adsorption structure; the air inlet pipeline is connected to the air inlets of the two reaction cabins and is close to the draught fan, the draught fan is used for sucking indoor air into the corresponding reaction box bodies and enabling the indoor air to flow through the heater and the carbon dioxide adsorption structure, and the carbon dioxide adsorption structure is used for adsorbing carbon dioxide in the flowing air; the heater is used for heating flowing air and desorbing carbon dioxide adsorbed in the carbon dioxide adsorption structure; and the two reaction cabins alternately perform adsorption and desorption of carbon dioxide. The device is convenient to operate and can continuously and efficiently control the concentration of indoor carbon dioxide.

The invention relates to the technical field of computer aided design, in particular to an energy-saving building design method based on digital simulation, which comprises the following steps: analyzing air velocity, temperature gradient, density and pressure distribution based on indoor aerodynamic parameters, identifying air vortex structure characteristics, and generating an energy-saving building environment data set. According to the method, aerodynamic characteristics in a building are accurately recognized, the vortex structure analysis capacity is improved, the air flowing path is optimized, aerodynamic parameters are combined, thermal resistance and heat conduction materials are matched, the building envelope layer is adjusted, heat flow transmission is guided, heat loss is reduced, the heat energy utilization rate is increased, and the spectral characteristics of the materials are adjusted according to illumination redundancy; the lighting efficiency is optimized, the heat load is reduced, outer wall heat transfer is optimized in combination with airflow characteristics, the ventilation rate is dynamically regulated and controlled, airflow short circuit is avoided, heat flow, illumination and ventilation parameters are integrated, precise optimization of building energy consumption is achieved, and the energy efficiency regulation and control level is improved.

In order to solve the problems of high energy consumption and unbalanced comfort of a traditional static control strategy of the air conditioning system during environment change, a building three-dimensional model is constructed, and sensor data and energy consumption simulation software are fused to construct a joint simulation environment. The improved extreme learning machine neural network is used for predicting the air conditioner energy consumption and the personnel thermal comfort degree, the network structure and parameters are optimized through the rotary particle swarm optimization, and the prediction precision and generalization ability are improved. And then, in combination with a Newton-Raphson multi-objective optimization algorithm, solving an air conditioner temperature set value optimal dynamic sequence in a rolling manner, and balancing energy consumption and comfort through a Pareto frontier solution set. Through dynamic simulation and data driving optimization, precise regulation and control of the air conditioner are achieved, and the thermal comfort degree is improved.

An indoor air cleaning system, including: plural gas detectors which are disposed in indoor and outdoor fields for detecting air pollution information and outputting through IoT; a circulation back-flow channel; a circulation filter device disposed in the circulation back-flow channel; an air conditioning device disposed in indoor field for temperature and humidity adjustment; and a cloud computing server device receiving the air pollution information through IoT to form a database of the air pollution information, and receiving the temperature and humidity information outputted from the air conditioning device. The cloud computing server device compares the database and the temperature and humidity information, and outputs a control command to enable the circulation filter device. Internal circulation directional airflows are generated in the indoor field, the air pollution is guided to pass through the circulation filter device multiple times, and the ZAPClean Room 1˜9 of indoor field is achieved.

The invention discloses a ventilation and air exchange device for a green building. The ventilation and air exchange device comprises a ventilation and air exchange box, a mounting plate, a ventilation and air exchange opening, a rotary air disc and fan blades. Mounting plates are fixed to the two ends of the two sides of the ventilation box, fixing pins penetrate through the interiors of the mounting plates, one ends of the fixing pins extend into the green building wall, and ventilation ports are formed in the two ends of the outer side of the ventilation box. According to the ventilation device for the green building, a fan motor is used for driving a linkage shaft to rotate, and a transmission assembly is matched to enable a fan shaft to rotate synchronously, so that two rotating wind discs and a plurality of fan blades are driven to rotate, outdoor fresh air is extracted and fed into the green building, and the ventilation effect is improved. According to the indoor air purification device, vitiated air, harmful gas and microorganisms in a building can be effectively diluted and discharged, so that the indoor air quality is improved, a healthier and more comfortable living environment is provided for people, indoor oxygen can be effectively supplemented, and the freshness and vitality of indoor air are kept.

The invention provides a fan coil control method and device, a medium, a fan coil and an air conditioning system. The control method of the fan coil comprises the steps that an indoor return air enthalpy value and a target enthalpy value are obtained; acquiring a required cold air ratio according to the indoor return air enthalpy value and the target enthalpy value; and the air supply amount of the fan coil is controlled according to the required cold air ratio and the refrigerant cold supply amount of the fan coil, so that the difference value between the real-time cold air ratio and the required cold air ratio of the fan coil is adjusted to be within the preset difference value range. By means of the technical scheme, the technical problem that in the prior art, a fan coil is poor in use comfort can be solved.

The invention discloses a method for predicting dynamic distribution of an indoor air flow field and a temperature field of a building. The method comprises the steps of performing grid division on a target space to obtain three-dimensional grid units, setting boundary attributes of the target space and initial values of air field parameters, and then obtaining vector velocities of the three-dimensional grid units according to an air transfer velocity between two three-dimensional grid units, then, according to the pressure intensity, the temperature and the air transfer speed of the three-dimensional grid units at the current moment, the pressure intensity, the temperature and the air transfer speed of the three-dimensional grid units at the next moment are obtained, and finally, the air flowing moment of the target space is continuously updated and iterated. And the distribution result of the air flow field and the temperature field in the target space in the air flowing process is obtained. The method is beneficial to improving the directivity of heating and ventilation design or air conditioning system adjustment, so that the efficiency of indoor environment quality optimization is improved, and effective assistance is provided for improving the comfort of a user and reducing energy consumption.

An indoor air cleaning system is disclosed and includes an air pollution treatment device, and a networked cloud computing service device. The air pollution treatment device includes an air cleaning device, a central control and regulation device and a communication module for detecting, locating, circulating and filtering the air pollution in an indoor field. A gas detection module detects and transmits air pollution data to the communication module. The central control and regulation device communicates with and controls the gas detecting module, to control the air cleaning device for filtration. The networked cloud computing service device receives and stores the air pollution data to form an database. A control command is intelligently selected, and transmitted to the gas detection module. Consequently, the air cleaning device is controlled to filter the air pollution, and a gas state in the indoor field reaches a clean room requirement of ZAPClean Room 1˜9.

1. The name of the product of this design: Air Purifier (C07). 2. Purpose of the product with this appearance design: The product with this appearance design is used for indoor air humidification, disinfection and purification. 3. The design key point of this appearance design product lies in the shape. 4. The picture or photo that best illustrates the design points: three-dimensional picture.

The invention discloses an indoor air filter, and relates to the technical field of air treatment, the indoor air filter comprises a machine body and an air duct, and further comprises a first partition plate, the top of the first partition plate is provided with a rotary drum, the outer wall of the rotary drum is provided with two through holes, and the through holes are internally provided with filter screens; the driving mechanism is used for driving the rotating drum to rotate; an air guide mechanism; a second partition plate; the linkage air control mechanism comprises an air cylinder mounted at the bottom of the second partition plate, a first piston mounted in the air cylinder and a lifting frame mounted at the top of the first piston; air is filtered by exchanging the two filter screens, the problem that in the prior art, the filter screens need to be cleaned after shutdown is solved, the continuous use effect of the air filter is guaranteed, the surfaces of the replaced filter screens are cleaned in a closed mode through the cleaning mechanism, and the cleaning efficiency is improved. And the directional dust removal mechanism is matched to timely and directionally guide out the cleaned dust impurities, so that the problem that the dust impurities are easily attached to the surface of the filter screen again and are difficult to clean thoroughly when the filter screen is cleaned is solved.

The invention discloses an indoor air quality inspection robot, which belongs to the field of indoor air quality inspection, and comprises the following steps: collecting air quality data in real time by adopting a sensor network according to preliminary monitoring priority distribution, extracting abnormal fluctuation characteristics from air quality change of each region, and determining a target region range needing key inspection; a path planning algorithm is called to generate a shortest feasible path from a current position to a target area through a local path adjustment scheme in combination with a global path optimization target, and a real-time updating result of a dynamic inspection path is obtained; and transmitting task allocation data of each inspection robot through a scheduling instruction of multi-device collaborative operation, and extracting target area and path planning information of each device from the task allocation data to obtain a coordination optimization scheme of overall inspection coverage.

A system can include one or more memory devices that can store instructions thereon that, when executed by one or more processors, cause the one or more processors to retrieve first information to indicate one or more aspects of a building, generate a plurality of constraints for a model, provide the plurality of constraints to the model to cause the model to simulate a performance of a plurality of sensors in collecting first indoor air quality data for the building, identify one or more first sensors to position at one or more first locations of the building and one or more second sensors to position at one or more second locations of the building, and generate a recommendation to indicate a placement of the one or more first sensors and a placement of the one or more second sensors.