5496 results about "Breathing" patented technology

The invention relates to the technical field of granary ventilation and energy consumption optimization, in particular to an intelligent granary ventilation and energy consumption optimization decision-making method based on reinforcement learning, and the method comprises the steps: obtaining the internal and external multi-dimensional state data of a granary, respectively constructing a basic state vector, a space correlation feature vector and a grain condition change trend vector based on the multi-dimensional state data inside and outside the granary; combining the basic state vector, the space correlation feature vector and the grain condition change trend vector into a space-time feature tensor, inputting the space-time feature tensor into a space-time topology perception decision model based on a graph attention network, and outputting an optimal composite action vector for controlling ventilation equipment; and analyzing and converting the optimal composite action vector to drive ventilation equipment of the granary to execute control. According to the method, through fusion of space-time topology perception and deep reinforcement learning, accurate prediction and active regulation and control of the granary state are realized, and energy consumption of a ventilation system can be reduced to the greatest extent while grain storage safety is ensured.

The invention relates to the field of heart rate monitoring, and discloses a millimeter wave radar breath and heart rate synchronous monitoring method and system, and the method comprises the steps: transmitting a linear frequency modulation continuous wave signal according to a millimeter wave radar, and collecting original echo data reflected by a target region; baseband signal demodulation and phase information extraction are carried out on the original echo data to obtain original phase time sequence data, and the original phase time sequence data comprise thoracic cavity micro-motion features; and according to a Butterworth band-pass filter, preprocessing the original phase time sequence data through human body physiological signal frequency band characteristics to obtain a breathing frequency band signal and a heart rate frequency band signal. According to the method, the apnea event triggering threshold value and the arrhythmia early warning index are updated in real time through Kalman filtering and extended Kalman filtering, so that the monitoring system can dynamically adjust the health parameters, which means that the monitoring system can be optimized in real time and the abnormal health event can be accurately responded in different physiological states.

In some implementations, a low dead space airway adapter for sampling fluid flowing through a ventilation assembly includes an outer wall configured to couple to an endotracheal (ET) tube adapter and an internal projection positioned at least partially within an internal cavity defined by the outer wall and configured to extend within an internal cavity of the ET tube adapter when the airway adapter is in use. The internal projection can include a fluid passageway configured for fluid communication with at least a portion of the internal cavity of the ET tube adapter and a free end comprising an opening in fluid communication with the fluid passageway. At least a portion of the free end can be chamfered around the opening and configured to contact an inner surface of the ET tube adapter when the outer wall is coupled to the ET tube adapter.

The invention relates to the field of mine ventilation, in particular to an intelligent adjusting method and system for mine ventilation. The method comprises the following steps: constructing a dynamic topology model taking a roadway as an edge and taking a fan and an air door as nodes based on a mine CAD drawing; acquiring the actual wind pressure and the actual wind volume of each roadway branch in real time, performing inversion to obtain the current wind resistance, and updating the wind resistance attribute of the edge in the dynamic topology model by using the current wind resistance; calculating the optimal air volume of the roadway branch by using the updated dynamic topology model; based on the optimal air volume, target regulation and control parameters of the draught fan and the air door are obtained through solving by means of a particle swarm algorithm; and according to the target regulation and control parameters, the fan and the air door are adjusted through a fuzzy PID algorithm. The problem that in the prior art, mine ventilation adjustment is not intelligent and safe enough is solved, the theoretical optimal air volume is obtained through deep analysis of the mine, then ventilation adjustment is conducted step by step, and the scientificity and efficiency of ventilation adjustment are improved.

The invention provides a mobile henhouse ventilation regulation and control method and system based on an environment model, and relates to the technical field of intelligent breeding, and the method comprises the steps: obtaining original temperature data, original humidity data, a three-dimensional space wind speed component, an opening geometric distribution data set, and original latitude and longitude coordinate data and time data; calculating a dynamic environment weight coefficient matrix according to the original latitude and longitude coordinate sequence and the time data; generating a self-adaptive heat exchange flow field according to the dynamic environment weight coefficient matrix, the original temperature data and the original humidity data; according to the self-adaptive heat exchange flow field and the trepanning geometric distribution data set, a ventilation compensation amount demand curve is obtained through calculation; generating a ventilation intensity adjusting instruction set according to the ventilation compensation amount demand curve; and according to the ventilation intensity adjusting instruction set, outputting an optimal ventilation control parameter. According to the method, ventilation response self-adaptive accurate matching, airflow dead zone self-suppression and energy consumption-effect dynamic balance under the moving sudden change working condition are achieved.

The invention relates to a dynamic regulation and control method and system for mine ventilation. The method comprises the following steps: acquiring multi-source data in a mine, and preprocessing the multi-source data to obtain a standardized data set; calculating the risk of each region in the mine based on the standardized data set to obtain a risk prediction matrix; based on the standardized data set and the risk prediction matrix, the air volume demand of each area is calculated, and an air volume demand table is obtained; based on the air volume demand table, an optimization proposition corresponding to the air volume demand is constructed and solved, and a solution set of the optimization proposition is obtained; mapping the solution set based on a preset rule to obtain a feasible allocation scheme; and based on the feasible allocation scheme, generating an equipment cooperation instruction, and obtaining a security instruction set. According to the method, dynamic factors can be considered, the air volume is dynamically adjusted, multi-fan cooperation is achieved, and the effects of real-time sensing and autonomous dynamic decision making of mine ventilation are achieved.

The invention relates to the technical field of biomedicine, and discloses a female private rehabilitation training system integrating a breathing method and neural motor control, and the system comprises a data collection module which is used for collecting physiological data of a user; the personalized training scheme generation module is used for generating a personalized nerve-muscle-fascia training scheme; the nerve-muscle synchronous resonance training module is used for constructing a time sequence matching model and generating an adaptive training dynamic control instruction; the space-time adaptability training module is used for adjusting training duration, intensity and stimulation frequency; the multi-dimensional nerve-muscle feedback fusion module is used for constructing a feedback response model; and the fascia synchronous activation and relaxation module is used for coordinating the tension relationship between the fascia and the muscle system. According to the method, feature matching is carried out on an electric activation heat map matrix through the convolutional neural network, analysis of a myoelectricity response state transition probability is carried out in combination with a hidden Markov model, and stimulation parameters and respiratory rhythm are optimized in real time according to a training process.

The invention relates to the technical field of mine environment control, and discloses an intelligent environment monitoring and control method in a mine laneway. The method comprises the steps that a real-time environment parameter set of a mine laneway is collected, the set contains gas concentration data, dust concentration data and temperature and humidity data, and real-time capture of laneway environment multi-dimensional parameters is achieved; then, based on the collected real-time environment parameter set, calculating an environment safety evaluation index so as to scientifically and objectively reflect the roadway environment safety condition; a dynamic control strategy is generated according to the environmental safety evaluation indexes, and the strategy comprises ventilation equipment regulation and control parameters and early warning level parameters and can be flexibly adjusted according to environmental changes; and finally, the ventilation equipment regulation and control parameters are sent to a mine ventilation system, and roadway environment regulation and control are executed. According to the method, environmental parameters can be comprehensively monitored, safety risks can be accurately evaluated, ventilation equipment can be flexibly regulated and controlled, the early warning function can be perfected, energy waste can be reduced, labor intensity can be reduced, and underground operation safety and mining efficiency can be guaranteed.

The invention relates to the technical field of medical care informatics, and discloses a laryngeal mask ventilation control method suitable for outpatient anesthesia, which comprises the following steps: before core analysis, injecting and monitoring a high-frequency signal to confirm the integrity of an original breathing waveform data stream; constructing a real-time ventilation waveform trajectory in a differential phase space only on the premise that a data stream is complete, and performing morphological comparison with an individualized baseline template; meanwhile, when a parameter adjustment event of the respirator is monitored, the baseline template is automatically re-calibrated, a collaborative analysis framework with front information source quality inspection and dynamic reference self-adaption capabilities is constructed, ventilation monitoring is converted from passive response to an isolated peak point into active insight to a system dynamics evolution trajectory, and the system dynamics evolution trajectory is optimized. Therefore, the risk of gradual deterioration of the ventilation state caused by tiny air leakage of the laryngeal mask or secretion accumulation can be clinically recognized in an early stage, and intervention time is won for anesthetists.

The invention relates to the technical field of biomedical engineering, and discloses an acute respiratory distress syndrome mechanical ventilation adaptive adjustment control system, which comprises a data acquisition module, a signal preprocessing module, a physiological parameter calculation module, a prediction module, a decision and control logic module and the like. Wherein the prediction module predicts a dynamic lung compliance change trend by using a long short-term memory neural network model, and the decision and control logic module generates a ventilation parameter adjustment instruction according to a prediction result and a clinical safety rule. By adopting the technical scheme, the system overcomes the hysteresis of traditional feedback regulation, reduces the risk of breathing machine related lung injury, optimizes oxygenation and carbon dioxide removal efficiency, and provides an accurate, safe and individualized mechanical ventilation treatment scheme.

The invention relates to the field of ventilation equipment early warning, in particular to a ventilation equipment early warning method and system for a smart laboratory, and the method comprises the steps: building a window with a target moment as a center, and obtaining a multi-dimensional state parameter sequence of ventilation equipment in the window; calculating the maximum cross correlation coefficient of the target moment, obtaining the optimal lag, weighting the optimal lag to obtain a final lag coefficient, and obtaining the cross correlation difference significance according to the maximum cross correlation coefficient of each sampling moment in the window; and aligning the state parameter sequences of different dimensions in the window based on the final lag coefficient, obtaining the correlation of the state parameter sequences of any two dimensions, calculating a risk value of the target moment, and correcting the risk value to obtain a risk correction value. According to the technical scheme, the early warning precision of the ventilation equipment can be improved, and the influence of hysteresis on early warning is reduced.

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 control systems, and discloses a vent valve control system with a pressure regulation function for a generator set, which is used for breaking through the limitation of static state, single target and passive response of a traditional vent valve control method. Comprising the following steps: acquiring pressure, flow velocity and valve opening data of a ventilation system in real time, generating a dimensionless parameter set for dynamic calibration, integrating parameter uncertainty disturbance terms to form a hybrid prediction model, solving an optimal valve opening instruction sequence by adopting a multi-target robust optimization algorithm, and designing a layered safety control mechanism. The system safety is guaranteed through dual-threshold monitoring and emergency intervention, redundant sensor data fusion and parameter reverse optimization are introduced, and fault tolerance and model self-adaption are achieved. According to the method, through collaborative innovation of dynamic modeling, robust optimization and intelligent fault tolerance, the control precision, the anti-interference capability, the safety and the reliability of the ventilation system of the generator set are remarkably improved, and the method is suitable for complex and changeable industrial operation scenes.

The invention belongs to the technical field of ablation puncture navigation, and particularly relates to an ablation puncture surgery navigation system under AI visual guidance. Through cooperative work of the phase monitoring module, the channel construction module, the needle moving control module, the displacement prediction module and the feedback control module, an intelligent surgical navigation system is constructed, breathing phase information and multi-modal medical image data of a patient can be obtained in real time, and therefore a safe and optimized needle moving path is accurately planned, and the operation accuracy is improved. Meanwhile, through real-time monitoring and quantitative evaluation of parameters such as tissue deformation and pressure distribution in the needle moving process, potential operation risks can be found and corrected in time, smooth operation is ensured, in addition, the system can dynamically adjust the needle moving path and the puncture angle according to the real-time breathing state of a patient, and the operation safety is improved. The accuracy and the safety of the operation are further improved, so that intelligent management and personalized treatment in the ablation puncture operation process are realized.

The invention provides a heating ventilation air conditioner control method, system and device based on dynamic heat load prediction and a storage medium. The method comprises the following steps: acquiring indoor individual physiological data, environmental parameters and regional personnel distribution data in real time; determining a real-time individual metabolic rate equivalent based on the individual physiological data and the environmental parameters; aggregating the individual metabolic rate equivalents according to the regional personnel distribution data, determining the total heat load and the total heat load change rate of each indoor region, and decomposing the total heat load into a sensible heat load and a latent heat load; and on the basis of the sensible heat load, the latent heat load and the total heat load change rate, air supply temperature, air supply amount and humidity control instructions of the heating ventilation air conditioning system for feed-forward adjustment are generated. According to the technical scheme, dynamic thermal load prediction based on individual physiological data and environmental parameters can be achieved, the indoor total thermal load is quantified in real time, and the feedforward adjustment control instruction of the heating ventilation air conditioning system is generated.

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.

Ventilation members for venting and / or draining moisture in building structures include a base panel and at least a transversely extending panel. Vent or drain openings are provided through the transverse panel, and a holding clip extends from the transverse panel for holding a drainage mat in place.

The invention relates to the technical field of medical prediction, in particular to a digital twinborn prediction method for patient lung protective ventilation supported by ECMO, which comprises the following steps: extracting flow velocity change and jump points under the support of ECMO, constructing a ventilation fluctuation trend map, identifying fluctuation sections by combining compliance and pressure value ratio, delimiting lung partitions and analyzing oxygenation ratio trend. And generating an oxygenation capability classification graph, sequencing ventilation path effects, and outputting a pulmonary protective ventilation digital twinborn prediction scheme. According to the method, dynamic response mapping of ventilation behaviors is established on the basis of timing sequence changes of breathing flow velocity jump characteristics and compliance pressure value ratios, the lung regional ventilation state is accurately recognized, lung function zoning division is achieved by combining oxygenation ratio waveform classification, ventilation path utility sorting is completed through oxygenation descending characteristics under path coverage, and the lung function evaluation accuracy is improved. And a path state prediction sequence is constructed by fusing the change relationship between the tensile stress and the ventilation pressure, so that the dynamic adaptability of the ventilation strategy to the lung mechanics and oxygenation state and the region matching precision are improved.

The invention discloses an anesthesia strategy generation system fusing time sequence data and a knowledge graph, and relates to the technical field of medical information processing. The method specifically comprises the steps that five types of vital sign data including arterial blood pressure, electrocardio and electroencephalogram are collected, correction is conducted in combination with traction marks and electrotome interference characteristics, and an analysis result is output; the inference analysis module executes double-track processing based on the analysis value, one track evaluates cortical suppression, shock and ventilation risks and generates a risk report, and the other track performs reverse arbitration when the blood oxygen data is abnormal; constructing a knowledge graph fusing the efficacy nonlinear cooperation equation, the age sensitive parameters and the drug administration sequence influence; and the strategy generation module integrates the multi-source data to generate a drug execution track, and executes fast and slow closed-loop regulation and control based on a risk report and an arbitration result. According to the invention, the adaptation capability of the system to individual differences, the abnormal signal identification and processing capability and the intelligent response level of the anesthesia strategy are improved, and the accuracy and safety of clinical anesthesia are significantly enhanced.

The invention belongs to the field of lung medical data processing and radiotherapy, and discloses a respiratory feature extraction method for chest and abdomen body surface point cloud partitioning by considering a lung physiological structure. After the body surface point cloud image is differentiated, correlation coefficient calculation is carried out according to a lung lobe model reconstructed by a lung 4DCT image, a body surface area highly correlated with a lung lobe structure is selected to carry out motion information dimension reduction recombination, and finally body surface global features of breathing are represented in a three-dimensional vector form. Compared with the prior art, the method has the advantages that the influence of the lung physiological structure on the lung tumor movement mode is creatively considered, meanwhile, the advantages of being noninvasive and free of extra dosage are kept, a new thought can be provided for development of the radiotherapy image guide technology, and further research in the field of thoracic and abdominal activity tumor radiotherapy is facilitated.

The invention relates to the technical field of physical sign detection, and discloses a far infrared radar non-contact physical sign detection method and device, and the method comprises the steps: collecting radar echo data and body temperature data of a plurality of target objects in a detection region through a far infrared sensor and a millimeter wave radar; carrying out heartbeat and respiration signal analysis on the radar echo data to generate a first heartbeat parameter and a first respiration parameter, and carrying out body temperature distribution analysis on the body temperature data to generate a body temperature distribution parameter; calculating a second heartbeat parameter and a second breathing parameter of each target object based on the first heartbeat parameter and the first breathing parameter; according to the second heartbeat parameter, the second breathing parameter and the body temperature distribution parameter, a physical sign detection result of each target object is generated, the abnormal heartbeat, breathing and body temperature states can be automatically recognized, a comprehensive health assessment result is generated, and the accuracy of non-contact physical sign detection is improved.

The invention provides a dynamic lung compliance monitoring method based on electrical impedance tomography, and the method comprises the steps: obtaining an electrical impedance signal and pressure-volume curve data, recording a time sequence signal of lung tissue in a dynamic ventilation process through a synchronous collection device, and obtaining an original multi-dimensional data set; aiming at the second feature set, eliminating redundant parameters by applying a feature screening mechanism, and evaluating the importance of each feature in different breathing stages through an information gain algorithm to obtain a third feature set; constructing a dynamic compliance monitoring model through the weighted feature set, and fitting a lung compliance change trend by using a support vector regression algorithm to obtain a real-time prediction result; and according to the updated prediction result, evaluating the improvement degree of the calculation efficiency, and judging whether the real-time performance meets clinical requirements or not by recording the model operation time and the resource occupancy rate so as to obtain final monitoring output.

The invention relates to the technical field of emotional robots, and discloses an embracing emotional robot which comprises an inner shell, low-cost and high-simulation breathing simulation is achieved through cooperative control of an air pump and an air valve, and the embracing emotional robot is designed by combining simulation body temperature brought by a heating piece and synchronous action of a rotatable arm. The emotion robot can naturally rotate forwards when being embraced and is matched with simulated respiration and simulated body temperature, so that the immersion and emotion interaction experience of a user are remarkably improved; the operation cycle of the air pump strictly follows biological breathing characteristics, the inspiration stage accounts for 2 / 3 of the breathing cycle, the speed of the inspiration stage changes fast and slow, the expiration stage accounts for 1 / 3 of the expiration stage, smooth pressure relief is achieved through the air valve, and the highly-simulated breathing mode can effectively guide a user to breathe synchronously, so that parasympathetic nerves are activated, the anxiety level and heart rate fluctuation are reduced, and the user experience is improved. And the whole structure adopts a modular design, complex functions such as breathing simulation, embracing and body temperature simulation can be realized, the maintenance is convenient, and the device is particularly suitable for long-term accompanying scenes.

The invention belongs to the technical field of acupuncture and moxibustion, and discloses a needle body tracking type intelligent acupuncture and moxibustion system which comprises a data collecting and processing module, a needle body positioning module, a 3D model registration and dynamic updating module, a real-time rendering display module and an interaction module. Three-dimensional coordinates, puncture depth and angle information of a needle body are obtained in real time with high precision through a multi-modal composite positioning technology, and real-time visual association of the needle body with key anatomical structures such as bones, blood vessels and nerves in the in-vivo penetrating process is achieved by combining a dynamically-registered 3D anatomical model and the actual body position of a patient. The needle inserting precision and the operation safety are obviously improved; meanwhile, through multi-plane fusion view presentation, a dynamic breathing compensation mechanism and a layered rendering updating strategy, it is ensured that a physician can visually master the real-time space relation between a needle body and surrounding tissue, and important structures are effectively prevented from being accidentally injured; and diversified touch interaction and instant operation feedback are supplemented, so that the operation complexity is greatly reduced.

The invention provides a ventilation system optimization method and system based on the air quality of an industrial aquaculture workshop, and relates to the technical field of environment regulation and ventilation system.The method includes the steps that aquaculture workshop gas is analyzed through an infrared spectrometer, the spectral intensity of the characteristic absorption wavelength of a target pollutant is obtained, and then the accurate concentration of the pollutant is analyzed according to the spectral intensity; and calculating a ventilation parameter reference value and controlling a fan to adjust the air supply amount. An air treatment device in the ventilation system can determine the optimal working time according to the air supply amount so as to decompose pollutants and continuously monitor the concentration of the pollutants at the inlet and the outlet of the device. Subsequently, the air quality deterioration index is predicted by analyzing the concentration change trend, and the current overall purification efficiency is calculated. When the purification efficiency deviates from the range or the deterioration index exceeds the threshold value, the running state of the device is dynamically adjusted and fed back to the system, self-adaptive optimization of the ventilation system of the industrial aquaculture workshop can be achieved, and it is guaranteed that the workshop air quality is stable and the purification efficiency reaches the standard.

The embodiment of the invention provides a real-time pulmonary ventilation impedance monitoring method and system based on multi-modal data fusion, and the method comprises the steps: obtaining real-time multi-modal data from a plurality of sensors, the multi-modal data comprising a sound signal, an airflow signal and a pressure signal; performing fusion processing on the multi-modal data to generate comprehensive pulmonary ventilation impedance data; based on the comprehensive pulmonary ventilation impedance data, analyzing data distribution characteristics to detect anomalies; and when abnormal data distribution characteristics are detected, a fault early warning system is triggered to solve burst signal distortion. Through the scheme of the embodiment of the invention, the problem of how to carry out fault early warning on the monitoring system according to the abnormal data distribution characteristics so as to solve the problem of burst signal distortion can be solved.

The invention belongs to the technical field of traditional Chinese medicine and software, and particularly relates to a traditional Chinese medicine syndrome differentiation aid decision-making method based on trans-modal attention Transform. The invention provides traditional Chinese medicine syndrome differentiation based on cross-modal attention Transform, and aims to explore a more scientific and systematic traditional Chinese medicine syndrome differentiation method by integrating multi-modal data such as visual sense, auditory sense, language, pulse condition and the like. Specifically, information such as complexion and tongue coating is obtained by inspection diagnosis through an image processing technology; the auscultation and diagnosis obtains sound information such as respiration and cough through a sound recognition technology; the inquiry analyzes the chief complaint and symptom description of the patient through a natural language processing technology; pulse condition data are collected through the sensor technology in the clinics. A multi-modal hierarchical dialectical logic framework is constructed, an exclusive attention mechanism is designed for each dialectical method, the overall view and dialectical thinking of traditional Chinese medicine are fully reflected, and a more reasonable dialectical result is generated.

The invention relates to the technical field of ventilation and dust removal, in particular to an energy-saving control method and system of a ventilation and dust removal system and a terminal.The method comprises the steps that the current operation condition of the ventilation and dust removal system is recognized through operation state parameters of all dust production devices; on the basis of the current operation condition and the working rhythm of each dust production device, predicting a dust production load change trend in a future time period; generating a header pipe air pressure value of the ventilation and dust removal system according to the dust production load change trend; according to the main pipe air pressure value, the fan operation frequency of the ventilation and dust removal system is adjusted, and the start-stop period of the ventilation and dust removal system is set, so that the technical problems of control response lag and energy waste caused by the fact that the dust production load change trend cannot be predicted by an existing energy-saving control method of the ventilation and dust removal system are effectively solved.

The invention particularly relates to an underground ventilation system, and belongs to the technical field of ventilation. The underground ventilation system comprises an air duct and a plurality of sliding rail assemblies. Each sliding rail assembly comprises a sliding rail part, a sliding part and a guide ring, the sliding rail parts of the multiple sliding rail assemblies are in butt joint in sequence, guide grooves are formed in the left side and the right side of each sliding rail part respectively, the guide grooves penetrate through the sliding rail parts in the length direction of the sliding rail parts, each sliding part comprises two oppositely-arranged wall parts, the sliding rail parts are arranged between the two wall parts, and the wall parts are rotationally connected with pulleys. The pulley is contained in the guide groove, and the guide ring is arranged corresponding to the sliding part and connected to the sliding part. The air channel sequentially penetrates through the guide rings. The system has the advantage that the air duct position is convenient to adjust.

The invention relates to the technical field of atomization rate control, in particular to an intelligent atomization compliance monitoring method and system for children. The method comprises the following steps: firstly, acquiring expiration flow velocity, inspiration flow velocity and multi-direction motion acceleration time sequence data of a child in a historical monitoring period, and reflecting breathing and behavior action conditions; dynamically analyzing the numerical characteristics of the expiration flow velocity and the inspiration flow velocity to divide a respiratory cycle, and analyzing the cycle length, the inspiration flow velocity cumulant and the like to construct a respiratory characteristic vector; screening a target monitoring period based on the breathing feature vector and the period number similarity; further analyzing the motion acceleration change and accumulation characteristics in the target monitoring period, and quantifying the behavior compliance expression degree; the behavior compliance expression degree and the breathing feature vector are deeply fused, a'breathing state-behavior cooperation 'joint evaluation model is established, the breathing and behavior states of children are dynamically recognized, the medicine atomization rate is accurately adjusted, and effective deposition of lung medicine is improved.