3574 results about "Indoor air" patented technology

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 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 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 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 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 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.

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.

The invention provides a method and a system for calculating carbon emission in a building operation stage, and relates to the field of carbon emission metering. The method comprises the following steps: acquiring model driving data in real time, wherein the model driving data comprises meteorological data in a building operation stage, heating system operation data, building use state data and power grid carbon emission intensity data; the model driving data are input into a third-order RC model to predict the dynamic energy consumption in the building operation stage and obtain energy consumption prediction result data, and the third-order RC model is a multi-region coupled model established according to the partition characteristics of the building structure and comprises indoor environment nodes, enclosure structure nodes, indoor air nodes and internal heat quality nodes; constructing a dynamic differential equation set according to a thermal network theory; and according to the energy consumption prediction result data and the dynamically updated carbon emission factor database, calculating to obtain corresponding carbon emission data. According to the technical scheme, accurate and real-time calculation of the carbon emission in the operation stage of the building can be achieved with low cost.

The invention provides a heterogeneous building air conditioner group quick response control method based on physical information deep learning, and the method comprises the steps: 1, obtaining a real-time discrete step scheduling instruction issued by a power grid, obtaining the thermodynamic parameters and equipment inertia time constants of all building units in a heterogeneous building group, obtaining the outdoor temperature, and carrying out the real-time discrete step scheduling instruction; the solar radiation intensity and the indoor air temperature of each building unit; step 2, extracting spatial-temporal characteristics of each building unit based on a multi-head self-attention mechanism, and generating initial distribution target power of the air conditioner; 3, inputting the initial allocation target power into a pre-trained cascaded physical information neural network (PINN), and predicting power and temperature evolution tracks in a future scheduling period; 4, calculating an out-of-limit risk index of each unit, judging whether to execute a quantile risk migration strategy or not, and generating a final distribution target power of the air conditioner; and 5, calculating the transient climbing deviation between the actual aggregation power and the target power of the power grid, and carrying out deviation compensation.

The invention discloses an automatic indoor air quality monitoring method, and belongs to the technical field of indoor air quality detection. According to the method, a first data set and a second data set are obtained by monitoring cells, air inlets and air outlets of a communication area and an indoor area, an air state model of the communication area and each indoor area is constructed, and a state transition probability and a state input probability are predicted and substituted into the air state model; and a state vector of the next state transfer step length is generated, so that the data processing amount of multi-region air quality monitoring is reduced, and the effect of prediction in advance is achieved. Furthermore, multiple components are monitored through an air state model, a negative parameter set is generated from the aspects of germ infection, lung harm, explosion danger and the like, the air quality negative index is evaluated, a positive parameter set is generated from the aspects of proper temperature and humidity, proper O2 concentration, proper CO2 concentration and the like, the air quality positive index is evaluated, and comprehensive monitoring of the air quality is achieved.

The invention relates to the technical field of environment monitoring, in particular to a multifunctional air quality monitoring and early warning system, which comprises a monitoring and adjusting module, a monitoring and early warning module, a monitoring and early warning module, an early warning module and an early warning module, and is characterized in that the monitoring and adjusting module monitors pollutants and temperature and humidity information in air through various sensors and automatically adjusts sensor detection ranges according to air quality conditions; the intelligent early warning module is used for establishing a prediction model, pre-judging the deterioration trend of the indoor air quality in advance through the prediction model, and triggering trend early warning when monitoring that the deterioration risk is high; and the equipment linkage module is used for establishing an equipment linkage rule base and automatically matching an optimal equipment operation strategy according to the air quality data. Various high-precision sensors are integrated, multi-dimensional data of particulate matter, harmful gas, oxygen content and temperature and humidity in air can be comprehensively monitored, the indoor air quality condition is accurately reflected, an air purifier and fresh air system equipment are automatically allocated according to a data analysis result, and intelligent environment adjustment is achieved.

The utility model discloses an air purification module applied to an air conditioner, the air conditioner is provided with a return air inlet and an air outlet, the air purification module comprises a mounting frame and a filtering device, and the filtering device is arranged on the mounting frame, corresponds to the return air inlet and is used for filtering air flowing into the return air inlet; the air purification module further comprises an air guide plate, and the air guide plate is arranged on the installation frame, corresponds to the air outlet and is used for guiding airflow flowing out of the air outlet. According to the utility model, the placing pressure is not increased, and the device is combined with the air conditioner to be used, so that indoor air is purified, fins of the air conditioner are protected to be clean, cleaning of the air conditioner is reduced, and microorganisms such as bacteria and molds in the air are reduced; meanwhile, air flowing through the air conditioner can be filtered at a time, the air outlet direction of the air conditioner is gently changed, and the problems that an existing air purifier is large in noise, large in occupied indoor space and low in air circulation efficiency are solved.

The invention discloses an energy-saving effect evaluation method and system for a high-rise building, particularly relates to the technical field of building energy conservation, and is used for solving the problems that in the prior art, a dynamic heat transfer delay effect is caused by neglecting thermal inertia of a glass curtain wall, and an energy-saving effect evaluation result is not accurate. The method comprises the following steps: acquiring outer surface temperature time sequence data of a target building glass curtain wall under various weather types and corresponding indoor air conditioner refrigeration energy consumption data; time sequence offsets of a daytime temperature peak value and a night energy consumption peak value are extracted period by period, and dynamic delay duration is calculated in combination with material heat transfer attenuation characteristics; night energy consumption data conforming to a stable delay threshold value are screened, and additional refrigeration energy consumption caused by daytime heat storage is quantified based on the delay time period weight; and finally, through dynamic weighted superposition of the daytime and night energy consumption data, an energy-saving evaluation result containing a heat transfer delay effect is generated. The evaluation deviation caused by night hidden load omission is avoided, and the reliability of the evaluation result and the engineering guidance value are improved.

Embodiments herein describe a method including using one or more air quality sensors and an air purifier to detect and adjust air quality within a structure having a heating, ventilation, and air conditioning (HVAC) system, the air purifier having a first variable speed fan in an intake channel and a second variable speed fan in an exhaust channel, and, in response to detecting an adverse air quality event within the building envelope by one or more sensors, automatically adjusting a speed of the first variable speed fan and a speed of the second variable speed fan (i) to maintain an air flow ratio between air inflow and air outflow within the HVAC system, (ii) to introduce increased fresh and filtered air flow from outside, (iii) to increase filtration of indoor air, (iv) to monitor the ERV and filter performance, and (v) to send relevant maintenance notifications to the user.

The invention provides an existing building BEM modeling method, system and device based on an infrared thermal image of an unmanned aerial vehicle and a medium, and belongs to the technical field of building modeling. Generating a three-dimensional geometric model of the building main body; screening out an external window candidate area by analyzing RGB value characteristics of the visible light point cloud, generating a window opening three-dimensional boundary, and determining an internal surface temperature and an indoor air temperature through internal surface infrared temperature measurement and area weighted integration; and based on the temperature data and the building envelope construction parameters, inverting heat transfer coefficients of the outer wall, the roof and the outer window, and finally constructing a building energy consumption model in combination with the weighted average K value. According to the method, precise operation from building geometric model construction to thermal parameter acquisition and then building energy consumption model construction is realized. The efficiency and precision of BEM modeling of the existing building are improved, and a scientific basis is provided for building energy-saving transformation, energy consumption evaluation and the like.

The invention relates to the technical field of fresh air blowers, and discloses a whole house type frequency conversion fresh air dehumidification system which comprises an intelligent control module, an environment sensing module, an intelligent control module, an intelligent control module, an intelligent control module, an intelligent control module, an intelligent control module and an intelligent control module, the indoor air quality data collection module collects indoor air quality data in real time and transmits the indoor air quality data to the intelligent control module, the air processing module comprises a fresh air introduction unit, a return air circulation unit and a mixed air processing unit, and the mixed air processing unit is configured to mix outdoor fresh air and indoor return air according to a preset proportion; according to the whole house type variable frequency fresh air dehumidification system, the variable frequency compression unit and the variable frequency fan unit are adopted, the humidity control precision of + / -3% can be achieved within the daily dehumidification amount range of 45-145 L, meanwhile, energy consumption is reduced by 15-35%, noise is lower than 36 dB (A), the PM2.5 purification efficiency of double filter screens reaches 99.98%, the indoor air quality is remarkably improved, and the maintenance process is simplified.

1. Name of the product in this design: Aromatherapy Humidifier Bluetooth Speaker (Jellyfish-Y20). 2. Purpose of this design: for playing audio, aromatherapy, and increasing indoor air humidity. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model.

The invention belongs to the technical field of intelligent control, and particularly relates to an air purification system based on intelligent perception and a self-adaptive regulation and control method thereof. Comprising a multi-dimensional environment perception unit, an environment data fusion and modeling unit, a self-adaptive regulation and optimization decision unit, a modular air purification execution unit and a man-machine interaction and user preference setting unit. According to the method, multi-element parameters are collected, fusion modeling is carried out, a pollution source is identified and predicted, a multi-target optimization algorithm is applied to generate an optimal purification strategy, and then a purification execution unit is controlled. The indoor air quality can be finely and dynamically managed, the purification efficiency is remarkably improved, energy consumption, operation noise and the service life of a filter material are intelligently balanced, and a personalized healthy breathing environment is provided.

The present application relates to air conditioning technology field, specifically relates to a kind of partition regulation formula refrigeration constant temperature and humidity air conditioning unit with air supply system, comprising: unit machine case;Constant temperature air supply structure for temperature regulation for air supply system air supply is equipped in the inside of unit machine case, and the air supply end of constant temperature air supply structure is connected with air duct for wind force transmission;The air duct is installed with constant humidity partition regulation structure for indoor partition regulation air supply in air outlet end.This application, in hot air heating mode, system can effectively deliver hot air to each partition by closing No. 1 and No. 3 electromagnetic valve, realize subarea heating, improve energy utilization efficiency, in cold air refrigeration mode, system is adjusted closed flap and starts compressor, so that cold air is delivered to each partition after refrigeration cycle, also realize subarea refrigeration, exhaust air and dust mode can extract indoor peculiar smell and dust, improve indoor air quality.

The utility model provides an anti-condensation and anti-icing exhaust air pipe which comprises an indoor air pipe and an outdoor air pipe. The air exhaust direction is from the front end to the tail end, the cross section of the indoor air pipe is gradually reduced in the air exhaust direction, and the front end of the indoor air pipe is located indoors and connected with an air exhaust fan; the tail end of the indoor air pipe extends outdoors; the outdoor air pipe and the indoor air pipe are coaxially arranged; the outdoor air pipe comprises an outdoor air pipe body with the equal cross section, an outwards-turned horn-mouth-shaped turned edge is further formed at the front end of the outdoor air pipe body, the tail end of the indoor air pipe is sleeved with the outwards-turned horn-mouth-shaped turned edge, a gap is formed between the outwards-turned horn-mouth-shaped turned edge and the outer wall of the tail end of the indoor air pipe, and an outdoor induced air flow channel is formed. The utility model provides a novel air exhaust duct structure, which effectively prevents the phenomena of air exhaust condensation and freezing through special design, ensures the normal operation of an air exhaust system, reduces the risk of ground freezing, and ensures that the air exhaust system can safely and efficiently operate in winter.

The utility model discloses a two-way air inlet integrated cooling cabinet, which relates to the technical field of energy conservation and emission reduction of air conditioners, and comprises a cabinet body, air supply pipelines and a two-way air inlet air conditioner, the air supply pipelines are positioned on the side surface of the cabinet and are in one-to-one correspondence with air inlets of electronic equipment in the cabinet body to form direct circulation of cold air; the bidirectional air inlet air conditioner comprises a first centrifugal fan and a second centrifugal fan, the first centrifugal fan and the second centrifugal fan are arranged in parallel, the first centrifugal fan is provided with a first centrifugal fan air inlet, and the second centrifugal fan is provided with a second centrifugal fan air inlet. One of the first centrifugal fan air inlet and the second centrifugal fan air inlet faces the front side face of the cabinet body, the other one faces the rear side face of the cabinet body, indoor airflow circulation is promoted, a local high-temperature area is prevented from being generated on one side of the cabinet, and therefore the overall good cooling uniformity and cooling effect are guaranteed.

A window-type air conditioner according to an example embodiment may include: an outdoor module including a compressor that compresses a refrigerant, an outdoor heat exchanger in which heat exchange occurs, and an outdoor housing; an indoor module including an indoor housing spaced apart from the outdoor housing, and disposed inside the indoor housing; and a connection module arranged between the outdoor module and the indoor module to connect the outdoor module to the indoor module in a thickness direction of a window included in a window frame, wherein the connection module includes a refrigerant pipe that provides a path for the refrigerant to move between the outdoor module and the indoor module, and a total heat exchange module that provides a discharge path for discharging indoor air to outdoors and a suction path for suctioning outdoor air to indoors, and performs indoor ventilation through heat exchange between the indoor air moving along the discharge path and the outdoor air moving along the suction path.