26 results about "Air mass" patented technology

The invention relates to the technical field of data detection, in particular to an unmanned aerial vehicle atmospheric data anomaly detection and correction system based on deep learning, and provides the following scheme: an air mass reference coordinate system is constructed based on the attitude of an unmanned aerial vehicle and a relative wind direction; re-projecting the original measurement data to obtain an atmosphere data sequence with a stable reference direction; then, generating a frequency mask dynamically changing along with time, wherein the frequency mask is used for constraining positioning of disturbance energy of the rotor wing in the time-frequency analysis process; performing multi-scale decomposition on the time-frequency coefficient matrix based on a multi-channel frequency mask, and respectively extracting an aerodynamic disturbance estimation signal, a background atmosphere signal and a turbulence structure signal; and inputting the three types of signals into a preset deep learning model to realize identification and corresponding correction of atmospheric data anomaly. According to the invention, rotor disturbance and a real atmospheric structure can be distinguished, and the quality and reliability of atmospheric observation data are improved.

The invention discloses an atmospheric pollutant traceability method and system based on trajectory clustering. The method comprises the following steps: collecting hourly pollutant concentration data and synchronous meteorological data of a target monitoring station during a pollution event; based on the meteorological data, calculating an air mass backward track arriving at the target monitoring station; carrying out preprocessing and clustering analysis on the backward trajectory of the air mass to obtain a plurality of trajectory clusters; aiming at each track cluster, potential pollution source contribution analysis related to the cluster is respectively carried out, and potential source area space distribution information corresponding to the cluster is identified and generated based on an analysis result; extracting a central track of each track cluster as a typical transmission path, and analyzing vertical transmission characteristics of pollutants of different air mass types; and generating a traceability map for assisting in formulating a differentiated regional joint defense and joint control scheme for different transmission paths and source regions. The mixed pollution source can be effectively deconstructed, and the source area and the conveying channel can be accurately associated.

The invention relates to the technical field of atmospheric science and remote sensing, in particular to a volcanic sulfur dioxide vertical section inversion method based on a Lagrange diffusion model, and the method comprises the steps: obtaining volcanic eruption total mass constraint, satellite sulfur dioxide column concentration and effective pixels, three-dimensional meteorological driving data and chemical clearing parameters; calculating a vertical weighting function by utilizing a radiation transmission mode, and generating initial vertical distribution by combining with a column concentration layering ratio; constructing a diffusion model to simulate an air mass backward track and match observation pixels to obtain attribution air mass distribution; optimizing a volcanic sulfur dioxide vertical emission profile time sequence based on attribution distribution and total mass constraint; and inputting the sequence into a diffusion model for forward simulation, comparing satellite observation data to calculate a verification index, correcting a diffusion coefficient according to a threshold value, and outputting a target vertical emission profile time sequence. According to the method, through backward trajectory attribution and forward verification closed-loop optimization, the volcanic sulfur dioxide vertical distribution inversion precision is remarkably improved.

The invention discloses a bionic air-space cooperative atmosphere intelligent regulation and control system and method. The system comprises a twin digital earth, an atmospheric brain, an air-space AI mobile base comprising a troposphere special base and a stratosphere special base, a plurality of macroscopic telescopic pipelines, an array composed of macroscopic intelligent sunshade reflectors, and a multifunctional intelligent micro-unit cluster. A regulation and control strategy is generated through multi-source data assimilation and intelligent strategy optimization, physical states such as temperature and humidity of air masses in a pipeline are actively adjusted through an environment control section in a macroscopic telescopic pipeline, and low-energy-consumption, stepped and directional transportation of cloud water substances is achieved by actively utilizing the chimney effect formed by the atmospheric environment; controllable adjustment of solar radiation input is achieved through dynamic management of the intelligent sunshade reflector array. The system has four operation modes which can be evolved according to technical capability stages from macroscopic direct intervention to global intelligent collaboration, and is configured with a module recovery and platform stability anchoring mechanism so as to realize emergency intervention on disastrous weather.

The invention relates to the technical field of fog potential forecasting, and discloses a plain area fog potential forecasting method based on weather typing and meteorological element change, which comprises the following steps: constructing a low-visibility event instance library, and establishing a high-altitude circulation and ground situation typing library; and then matching the real-time forecast field with the typing library to determine a weather background, and extracting meteorological elements such as temperature inversion and quiet wind. The method is characterized in that a movable boundary conceptual model is integrated, an air mass boundary is identified by calculating a horizontal temperature gradient and is quantified into discrete state characteristics representing cold and warm air mass effects, and finally, a weather background, conventional elements and the discrete state characteristics are jointly input into a Bayesian probability model, so that the air mass effect is obtained. And calculating and outputting the posterior probability of each fog potential level. According to the method, the key physical process is quantified and then fused into the statistical model, so that the capturing capability of a specific fogging mechanism is improved, and the forecasting result has high accuracy, strong interpretability and refined probability characteristics.

The invention relates to the technical field of vehicle-mounted mobile meteorological detection, in particular to a vehicle-mounted mobile meteorological detection system and method. The method comprises the following steps: activating a laser radar system of a vehicle-mounted end to collect back scattering signals of a target air mass corresponding to each collection point on a voyage route, performing inversion based on the back scattering signals to obtain an extinction coefficient of the target air mass, and determining the boundary of the target air mass based on the variation of the extinction coefficient of the target air mass on the voyage route; determining a wind field vertical profile of the target air mass based on the heterodyne spectrum; and obtaining a posterior failure probability of the moving trend of the target air mass based on Bayesian inversion analysis, and predicting the moving trend of the target air mass based on the posterior failure probability. According to the method, the air mass boundary can be accurately determined, the height of the vertical profile of the wind field is calculated, the air mass moving trend is analyzed and predicted through Bayesian inversion, and the accuracy of air mass moving trend prediction is improved.

The application discloses an iterative bias correction method considering non-uniformity of a satellite instrument probe element, which comprises bias correction amplitude, construction of a cost function and initialization, construction of a bias operator, clearing of the probe element bias, updating of an atmospheric quality bias correction BC coefficient according to an observation background deviation O-B, calculation of an observation background deviation O-B residual as the probe element bias by using the updated atmospheric quality bias correction BC coefficient, calculation of the next round of observation background deviation O-B according to the probe element bias of the last round, repetition of the probe element bias calculation step, multiple iterations until the atmospheric quality bias correction BC coefficient is stable, and output of the final atmospheric quality bias correction BC coefficient and the probe element bias for bias correction on observation data. The method makes the air mass bias correction coefficient and the probe element bias tend to be stable, improves the normality of the deviation between the initial guess observation and the simulation result, and makes the peak value and the average value closer to zero, and can be used for solving the probe element non-uniformity problem of the satellite instrument and the infrared hyperspectral probe.

The invention discloses a low-temperature humidity control method for an automobile environment test chamber, which relates to the technical field of automatic control of test chambers and comprises the following steps: acquiring dry-bulb temperature, relative humidity and atmospheric pressure in the chamber, front and back pressure difference of a coil pipe, air volume, surface temperature of the coil pipe and outlet temperature of the coil pipe, and calculating air mass flow and moisture content in the chamber; symmetrical temperature perturbation is applied with the current coil pipe surface temperature as the center, coil pipe air side channel impedance coefficients are calculated at different temperature points, and an impedance curvature index is calculated according to the coil pipe air side channel impedance coefficients; a continuous inhibition factor is generated based on the impedance curvature index, a basic dehumidification demand obtained by the moisture content deviation is continuously corrected, and a planned dehumidification mass flow rate is obtained; and the humidification mass flow rate, the coil pipe target temperature and the reheating power are further calculated and issued to a refrigerating loop, a humidifier and a reheater. The low-temperature humidity control stability of the test chamber can be improved.

This invention discloses an adaptive constant temperature control method and system for circulating water pumps based on ambient temperature, relating to the field of adaptive constant temperature control. The method involves acquiring the spatial structural parameters of an air conditioning cooler, constructing a three-dimensional thermal and humid air motion model coupling exhaust and intake airflows, generating a potential energy field for the risk of exhaust hot and humid air mass recirculation based on the three-dimensional thermal and humid air motion model, and combining real-time ambient temperature, forecast temperature, and meteorological boundary conditions to perform recirculation self-excited oscillation detection. A corrected equivalent ambient temperature is output to eliminate recirculation self-interference deviation. Using the corrected equivalent ambient temperature as a feedforward variable, a target operating current setpoint for the water pump is generated through a compensation function that compensates for the inverse relationship between the pump operating current and ambient temperature. After smoothing and filtering, the setpoint is output to the variable frequency drive of the circulating water pump. The variable frequency drive adjusts the output frequency according to the current setpoint to ensure that the pump operating current tracks the setpoint, maintaining a constant cooling water supply temperature.

The invention provides an air source heat pump frosting rate prediction method and system, and belongs to the technical field of air source heat pump defrosting control. The method comprises the steps that initial parameters needed by prediction are obtained, wherein the initial parameters comprise the outdoor air temperature and relative humidity, the outdoor heat exchanger coil pipe surface temperature and relative humidity and the outdoor heat exchanger air inlet speed; determining air state parameters at the outlet of the outdoor heat exchanger through iterative calculation on the basis of the initial parameters in combination with a linear relation of humid air state change in the enthalpy-humidity diagram; and finally, the real-time frosting rate is calculated according to the air moisture content difference, the air mass flow and the heat exchange area of the inlet and the outlet of the outdoor heat exchanger. The system comprises a corresponding parameter acquisition and calculation module. According to the method and system for predicting the frosting rate of the air source heat pump, accurate dynamic prediction of the frosting rate is achieved through theoretical modeling and iterative optimization, a reliable basis can be provided for intelligent defrosting control, and therefore the defrosting accuracy rate and the overall energy efficiency of the system are improved.

The application discloses a test method for starting flow velocity of a long-distance water pressure pipeline air mass, which comprises the following steps: acquiring corresponding geometric parameters of air masses with various geometric sizes and actual starting velocities for driving the air masses to move by tests; calculating characteristic lengths of the air masses by using various characteristic length calculation methods of the air masses according to the geometric parameters, and calculating drag coefficients based on the characteristic lengths; calculating theoretical starting flow velocities by using a starting flow velocity model of the air masses according to the drag coefficients of the air masses with various sizes and various forces in water; calculating relative errors between the actual starting velocities corresponding to each size and the theoretical starting flow velocities corresponding to different characteristic length calculation methods, and drawing a relative error curve corresponding to the same characteristic length calculation method; constructing a characteristic length calculation model of the air mass according to a change trend of the relative error curve, updating the drag coefficients by using the characteristic length calculation model, and then updating the starting flow velocity model.

The application provides a graphical data display method and a computer device, the method comprising: acquiring monitoring data representing atmospheric components of a monitoring site within a specified time period, and trajectory data representing a moving path of an air mass passing through the monitoring site at any target moment within the specified time period; graphically displaying a display interface comprising the monitoring data and the trajectory data; wherein the display interface comprises a parent graph generated by the monitoring data within the specified time period, and a subgraph generated by the trajectory data at any target moment; the subgraph and the parent graph have a correlation relationship at the same target moment. By displaying the monitoring data of the atmospheric components and the corresponding trajectory data in the same display interface, the relationship between the change of the atmospheric components and the movement of the air mass can be more intuitively displayed, which is beneficial to researchers to carry out spatiotemporal fusion analysis.

The present application relates to heat mass exchange equipment detection technical field, disclose a kind of method and device for testing packing performance, method includes the following steps: adjusting system to run to dynamic heat balance state;Utilize air state detection mechanism to carry out physical mixing sampling to cross section air to obtain average dry-wet bulb temperature, and simultaneously collect inlet and outlet water temperature;Air is shaped after passing through flow equalizer, average dynamic pressure is collected through physically connected wind pressure detector and actual air mass flow is calculated;Based on the acquisition parameter, according to heat transfer mass transfer theory, the numerical integral is carried out to calculate packing performance test constant;Finally, through multi-working condition test and curve fitting, general performance characteristic equation is established.The present application effectively solves the measurement error problem caused by airflow distribution uneven by air physical mixing sampling and airflow homogenization pressure measurement, improves the accuracy of thermodynamic parameters and flow calculation, and the characteristic equation generated has higher engineering application value.

The application discloses an atmospheric pollution tracing method fusing a numerical model and an artificial intelligence algorithm, and relates to the technical field of atmospheric pollution tracing. The method preprocesses meteorological data and simulates a high-precision meteorological field, converts a result into a readable format of a Lagrangian diffusion model, generates a high-resolution space-time footprint matrix based on the driving model, identifies a dominant air mass path, combines pollutant concentration data of receptor points, constructs and verifies a random forest regression model, takes the footprint matrix as features, takes standardized concentration as labels, quantifies the contribution of grid points through feature importance and Shapley explanation methods, and identifies key pollution source areas. The application can achieve the technical effect of significantly improving the accuracy and efficiency of atmospheric pollution tracing and providing more scientific and accurate decision-making basis for atmospheric pollution prevention and control.

The invention belongs to the field of explosive mechanics, and provides an explosive particle jet intensity calculation method and related equipment. According to the method, under the condition that high-pressure air mass drives explosive particles to move, a first cloud and mist area is determined according to mass distribution of the explosive particles, and a first jet flow area is determined according to the stacking density gradient of the explosive particles and the first cloud and mist area; calculating a first mass proportion of the explosive particles in the first jet region based on the mass of the explosive particles in the first jet region and the mass of the explosive particles in the first cloud region; determining the local stacking density of the explosive particles at the position of each jet flow in the first jet flow area and the minimum stacking density of the explosive particles in the first jet flow area; based on the first mass specific gravity, the local stacking density and the minimum stacking density, the first jet flow intensity is obtained. The method can accurately determine the jet flow intensity of the explosive particles.

The invention discloses an actual measurement-based rapid source tracing method for atmospheric particulate pollution, and belongs to the technical field of rapid source tracing methods for atmospheric particulate pollution. A regional particulate emission information base is established, and the information base comprises particulate emission amounts and spatial distribution of industrial, traffic, construction site dust raising and non-road mobile machinery departments; the method comprises the following steps: determining a particulate matter pollution period according to monitoring data or a forecast result; simulating regional meteorological characteristics of the pollution period by using a meteorological mode; acquiring meteorological data; determining a receptor position; and determining a pollution emission source area according to the pollution source identification parameters, and screening targeted prevention and treatment objects of particulate matter pollution.

The invention discloses an iterative deviation correction method considering satellite instrument probe element heterogeneity, which comprises the following steps of: correcting amplitude by deviation, constructing a cost function and initializing, constructing a deviation operator, clearing probe element deviation, and updating an atmospheric quality deviation correction BC coefficient according to an observation background deviation O-B, the updated atmospheric quality deviation correction BC coefficient is adopted to calculate the observation background deviation O-B residual error as the detection element deviation, the observation background deviation O-B of the next round is calculated according to the detection element deviation of the previous round, the detection element deviation calculation step is repeated, iteration is conducted for multiple times till the atmospheric quality deviation correction BC coefficient is stable, and the detection element deviation is obtained. And outputting the final air quality deviation correction BC coefficient and the detection element deviation to carry out deviation correction on the observation data. According to the method, both the air mass deviation correction coefficient and the detector deviation tend to be stable, the normality of deviation of initial guess observation and simulation results is improved, the peak value and the average value of the deviation are closer to zero, and the method can be used for solving the problem of non-uniformity of detection elements of satellite instruments and infrared hyperspectral detectors.

The invention provides a downburst maximum vertical wind speed diagnosis method and system, and the method comprises the steps: obtaining meteorological element data of a target high-voltage power transmission corridor with sparse meteorological data, extracting an environment temperature profile based on the meteorological element data, and determining the starting height and ending height of a sinking air block in downburst according to the meteorological element data; according to the initial height, the final height and the dry adiabatic rate change, a sinking air block temperature value changing along with the height is obtained; based on the initial height, the end height, the temperature numerical value set and the environment temperature profile, effective potential energy of sinking convection is calculated according to numerical integration; identifying the maximum value of sinking convection effective potential energy in a preset time sequence; based on the law of conservation of energy, the maximum value of effective potential energy of sinking convection is converted into the maximum vertical wind speed of downburst; according to the method, the diagnosis of the maximum vertical wind speed of the downburst is obtained by establishing a direct calculation method from the DCAPE to the maximum vertical wind speed of the downburst.

The application discloses a low-altitude atmospheric particulate matter rapid settling method and system, which acquires real-time multi-dimensional monitoring data, combines numerical prediction and air mass trajectory tracking technology, realizes three-dimensional dynamic identification of low-altitude particulate matter pollution air mass, significantly improves target area positioning accuracy, and effectively avoids invalid operation. The method of the application uses sound energy shock wave to impact the directional area, forms continuous turbulent disturbance in the open atmosphere, breaks through the suspended stable state of fine particulate matter, promotes particulate matter collision and natural settling, can realize wide-range and strong-disturbance treatment, and reduces pollution transmission influence.

Systems and methods are provided for circulating air and controlling air quality of an interior location. The system includes a compressor system for receiving air from the interior location, compressing the air, and supplying the compressed air to a desiccant system. The desiccant system removes moisture and contaminants from the air and delivers conditioned air to at least one expansion device. The expansion device then provides atmospheric level conditioned air back to the interior location.

The application provides a kind of meteorological element space-time representative calculation method and device, it is related to the technical field of meteorological element processing, including: obtaining meteorological element data of meteorological element guarantee target area preset period, and based on meteorological element data and preset clustering algorithm, meteorological element guarantee target area is divided into air mass;Based on meteorological element data, the spatial heterogeneity coefficient of each grid point in air mass is calculated;Based on the spatial heterogeneity coefficient of each grid point in air mass and preset meteorological guarantee precision, the spatial representative range of meteorological element data in air mass is calculated;Based on meteorological element data and EOF empirical orthogonal function, the time representative range of meteorological element data in air mass is calculated, the technical problems that the accuracy of existing meteorological element space-time representative calculation method is poor and space-time dimension is missing are solved.

The invention discloses a cloud base height forecasting method based on multi-factor dynamic analysis, relates to the technical field of meteorological numerical forecasting and atmospheric boundary layer analysis, and aims to predict the height of a cloud base by identifying the structural feature that the internal humidity of a mixed layer changes along with the height instead of only depending on the average relative humidity of the mixed layer in the cloud base height forecasting process. A continuous humidity increasing section is extracted, and the position of a potential condensation layer is determined, so that the initial condition of air block lifting calculation can more accurately reflect the actual water vapor distribution condition in the mixing layer. Under the condition that a local wet layer or a local high-humidity area exists, a wet layer structure closer to an actual condensation occurrence position can still be identified, so that the cloud base height calculation process is closer to a real atmospheric state; by calculating the thickness of the mixed layer, the vertical range of the mixed layer can be definitely limited, and the subsequent humidity structure analysis can be carried out aiming at the important region where the low cloud is formed, so that the cloud bottom height analysis process corresponds to the actual atmospheric boundary layer structure.

The invention belongs to the technical field of frozen soil roadbed engineering and intelligent temperature control, and particularly relates to a self-adaptive intelligent ventilation, temperature control and dehumidification system for a frozen soil roadbed and a regulation and control method. The method comprises the following steps: calculating an input cooling capacity value according to dry-bulb temperature and moisture content of an air pipe inlet and an air pipe outlet; the dehumidification amount is calculated according to the moisture content and the dry air mass flow; air is input into the air pipe according to the input cooling capacity and the dehumidification capacity; detecting temperatures of different depths of the roadbed, and determining depth values of 0 DEG C at different moments; subtracting the depth value at 0 DEG C from a set depth value at 0 DEG C to obtain frozen soil upper limit deviation; if the frozen soil upper limit deviation is larger than the preset threshold value, the input cooling capacity is adjusted, and the annual target and the monthly target of the input cooling capacity are adjusted. According to the method, a roadbed thermal condition rapid calculation system is constructed, inter-year and intra-year dual regulation and control targets are determined, and self-adaptive control is realized.

The invention relates to the technical field of radar detection, in particular to a Raman laser radar ozone three-dimensional real-time imaging method based on edge calculation, and the method can capture the influence of instantaneous temperature fluctuation on a signal through the independent deduction of the spectrum fidelity and the topological transformation potential energy, and can also capture the influence of the temperature fluctuation on the signal. The change of the continuous wind field to the air mass form can be accurately evaluated, and the contradiction of different physical processes on the space-time scale is solved; according to the method, the compression and turbulence intensity of the fluid is directly quantified by utilizing topological transformation potential energy, and sensing data is mapped into a standard three-dimensional GIS grid by utilizing a Lagrange trajectory backtracking algorithm and a Gaussian kernel function, so that blind areas among sensors are filled, each voxel data of the standard three-dimensional GIS grid is ensured to have a clear observation source, and the accuracy of measurement is improved. And the essential three-dimensional characteristics of the atmospheric environment are restored.

The invention belongs to the field of explosion mechanics, and provides an evaluation method for the dispersion degree of explosion particles, electronic equipment and a storage medium. According to the method, under the condition that high-pressure air mass drives explosive particles to move, a cloud and mist area is determined according to the distribution range of the explosive particles; determining the dispersion completeness of the explosive particles based on the mass distribution of the explosive particles in the cloud and mist area; determining the dispersion uniformity of the explosive particles according to the average bulk density of the explosive particles in the cloud area; and evaluating the dispersion degree of the explosive particles based on the dispersion completion degree and the dispersion uniformity. The method can accurately evaluate the dispersion degree of the explosive particles.

The invention provides a visual monitoring platform for air quality flow prediction, and relates to the technical field of air quality monitoring, and the platform comprises a data collection module which collects real-time monitoring data; the data processing center is used for acquiring air quality change indexes under different time nodes; the engine analysis module analyzes the working performance of the dust remover; the collaborative optimization operation module is used for acquiring a collaborative control queue; the risk early warning module is used for carrying out flow risk early warning on air quality in different subareas in the target area; and the visual interface is used for carrying out visual output. By means of the air quality monitoring method and device, the technical problem that the quality change of complex air is difficult to monitor in the prior art, so that the accuracy and timeliness of air quality monitoring are limited, and the air quality improvement effect is further affected can be solved. By constructing a collaborative operation and risk early warning system and enhancing a visual display function, the overall efficiency of air quality monitoring and management can be remarkably improved.