202 results about "Field observation" patented technology

The invention aims to provide a mine ecological restoration carbon sequestration rate prediction method for solving the problems of an existing ecological restoration carbon sequestration rate prediction method. The method comprises the following steps: step 1, collecting multiple parameter multi-source data including vegetation growth, earth surface change and soil change of an ecological restoration area; 2, integrating the data, and constructing a dynamic prediction model for the change of the mine ecological restoration carbon sequestration rate; 3, verifying and optimizing the prediction model by using historical data and field observation data; and 4, adopting a machine learning technical means for the optimized prediction model, and establishing a quantitative relationship between the carbon sequestration rate change and ecological restoration means of land utilization, vegetation coverage and soil attributes. The method overcomes the influence of extreme climate events on the carbon sequestration rate of an ecological system, can accurately predict the change trend of the carbon sequestration rate under different ecological restoration strategies in the future, and provides a powerful scientific basis for ecological restoration of a mining area.

The invention provides an ocean live big data fusion method based on deep learning, and relates to the technical field of ocean big data fusion, and the method comprises the steps: obtaining meteorological driving variables, ocean historical reanalysis data, satellite observation data and ocean field observation data, and performing unified format conversion processing on the basis of the acquired meteorological driving variables, the ocean historical reanalysis data, the satellite observation data and the ocean field observation data, and configuring a unified ocean environment feature tensor set. A unified marine environment feature tensor structure is configured, meteorological driving variables, marine historical reanalysis data, satellite remote sensing data and on-site buoy observation data are subjected to space resampling, time interpolation and missing complementation and are unified into a space-time grid under a geographic reference coordinate system, a four-dimensional tensor set is configured, and the four-dimensional tensor set is obtained. The problem of fusion obstacles caused by non-uniform data formats and inconsistent temporal-spatial resolutions in the prior art is effectively solved.

The invention discloses a complex terrain wind field multi-scale numerical simulation real-time assimilation method fusing external field measurement data, and the method comprises the steps: obtaining conventional meteorological and topographic data, determining a reference point, and carrying out the simulation of a complex terrain wind field numerical value based on a mesoscale WRF mode; acquiring external field observation data and high-precision terrain data, and improving the mesoscale numerical simulation precision of the complex terrain wind field based on a four-dimensional variational assimilation method by combining the high-precision terrain and the high-resolution grid until a first preset precision requirement is met; establishing a medium-micro scale coupling simulation framework based on WRF-CFD mode coupling, and performing high-fidelity CFD numerical simulation on the target wind field; and applying a four-dimensional variational assimilation technology to the CFD simulation process to improve the CFD numerical simulation precision to meet a second preset precision requirement. According to the invention, the precision of complex terrain wind field multi-scale numerical simulation can be improved.

The invention discloses a wheat yield remote sensing prediction method combining phenological parameters, which comprises the following steps: S1, performing field observation in a key growth period of winter wheat, synchronously collecting canopy hyperspectral reflectivity data, leaf area index (LAI) and SPAD value of each observation sample point, and recording wheat grain yield of the corresponding sample point; s2, performing noise reduction preprocessing on the acquired canopy hyperspectral data, and extracting sensitive spectral parameters by combining principal component analysis (PCA) and correlation analysis methods; s3, taking the sensitive spectrum parameters, LAI and SPAD values as independent variables, taking the wheat grain yield as a dependent variable, and adopting partial least squares regression (PLSR) to construct a multivariable yield prediction model; and S4, performing wheat yield prediction on an independent test sample or regional scale remote sensing data by using the trained model. The method overcomes the defect that only yield sensitive spectrum parameters are used for predicting the effect, and accurate estimation of the model is achieved.

The invention discloses a laboratory intelligent agent construction method and system based on artificial intelligence, and relates to the technical field of intelligent laboratories. In order to solve the problems of scattered laboratory data information, low scientific and technological resource matching efficiency, lack of a unified AI driving platform and the like in the prior art, a core agent is constructed by introducing machine learning or an artificial intelligence architecture, and digital access and resource pooling are carried out on scientific research total factors such as infrastructures, software and hardware, human property and the like. The intelligent agent is based on semantic alignment and inference rules, dynamic intelligent configuration of resources such as field observation, experimental analysis and computational simulation is achieved, and finally a full-life-cycle intelligent management and scientific research environment integrating equipment perception, intelligent control and business application is formed. According to the method, resource islands are effectively broken, the resource utilization efficiency is improved, a novel scientific research normal form of'big data + AI + model 'is promoted, and systematic support is provided for refined and automatic management of laboratories.

The invention discloses a marine environment spring layer characteristic diagnosis data processing method, and aims at complex dynamic characteristics of a land frame edge sea spring layer to realize accurate diagnosis through multi-source data cooperation and an intelligent algorithm. The method comprises the following steps: acquiring and preprocessing field observation, remote sensing, sonar, terrain and tidal ocean current data; extracting spatio-temporal characteristics based on a CNN-LSTM hybrid network, and generating a dynamic spring layer threshold; fusing multi-source data by adopting an improved D-S evidence theory, and constructing a three-dimensional spring layer characteristic field; predicting an internal wave in combination with an attention mechanism model, and optimizing a preorder model by using sonar data. The method breaks through the limitation of a fixed threshold value, realizes spring layer dynamic identification, three-dimensional reconstruction and internal wave prediction, improves the diagnosis precision of a complex sea area, and provides key technical support for underwater detection, engineering safety and environmental research.

After earthquakes, buildings experience damages at different levels depending on various parameters. The extent of damage is determined based on observations such as cracks in structural elements, material crushing, and reinforcement damages. Decisions made are crucial for ensuring human safety and preventing economic losses. The invention pertains to a system which comprises a mobile application containing an automatic decision support system capable of assisting experts conducting field observations after earthquakes and performing damage classification at the element level.

The invention discloses an ionosphere TEC forecasting method, system, medium and equipment fused with a geomagnetic field, and belongs to the field of ionosphere TEC forecasting, the method comprises the following steps: obtaining current ionosphere TEC grid data, solar activity index data and global geomagnetic field observation data, and constructing to obtain multi-channel fusion data; based on a preset ConvLSTM model, processing the multi-channel fusion data, and outputting an ionized layer TEC forecast result; wherein the ConvLSTM model is obtained by training an input sequence in historical multi-channel fusion data and a corresponding target sequence; the input sequence is composed of multi-channel fusion data of a plurality of consecutive time steps, and the target sequence is composed of ionized layer TEC grid data immediately after the input sequence. By implementing the method, the forecasting precision of the ionized layer TEC under complex space weather conditions such as magnetic storm can be improved.

The invention relates to a coastal zone sediment erosion pore scale flow field observation system and observation method. The observation system comprises a wave-flow water tank, a sediment accumulation body arranged in the wave-flow water tank and PIV equipment used for observing the internal flow field and the pore size of sediment. A wave making plate and a wave dissipating plate opposite to the wave making plate are arranged in the wave flow water tank, experimental fluid used for simulating waves is arranged between the wave making plate and the wave dissipating plate, and a wave height meter floats on the experimental fluid; the sediment accumulation body is formed by accumulation of transparent solid particles with the same refractive index as the experimental fluid; the PIV equipment comprises a laser light source and a camera, the laser light source is focused on the sediment accumulation body, and the camera directly faces the sediment accumulation body and is used for collecting images. Compared with the prior art, a clearer sediment pore internal flow field image is obtained through the combination of the refractive index matching technology and the image particle velocity measurement method, so that effective observation of the pore scale flow field eroded by the sediment in the coastal zone is realized.

The invention discloses a silty silt seabed critical start calculation method considering seabed liquefaction influence, and belongs to the technical field of silt dynamic simulation and calculation. The method comprises the following steps: firstly, acquiring wave parameters such as wave height, period and water depth, and calculating a characteristic Reynolds number based on a Stokes wave theory; in combination with field observation or indoor test data, the liquefaction grade is calculated through an empirical function, and the bed state is divided; then according to the liquefaction grade, the sediment erosion coefficient and the critical starting stress are corrected in an index form; and finally, correcting empirical coefficients by using field and indoor data, and constructing a regional correction coefficient table. The method can accurately reflect the influence of liquefaction on sediment starting, the accuracy of the calculation result is improved compared with that of a traditional method, the method can adapt to different sea area environments, operation is easy and convenient, and a reliable basis is provided for offshore engineering design and sediment movement prediction.

The invention discloses a rare metal mineralization potential comprehensive evaluation method based on rock geochemistry, and aims to solve the problems of single evaluation index and disjunction between field observation and indoor analysis in the prior art. The method comprises the following steps: obtaining geological data of an analysis area, and screening a target area based on a favorable structure background and an exposed feature criterion; identifying mineralogical and lithofacies markers and collecting sampling data; the method comprises the following steps: acquiring rock geochemical data of a sample sampled by a previous person, including multi-dimensional data including major elements, trace elements, isotope composition and the like, and calculating a quantitative evaluation index according to the data; and finally, establishing a comprehensive evaluation model by adopting a weighted scoring method to realize mineralization potential grade division and target region accurate delineation in a three-dimensional space. According to the method, organic combination of macroscopic geologic features and microcosmic geochemical data is realized, and a complete technical system from field observation to indoor analysis to engineering decision is formed.

The invention discloses a full-process control method and system for galvanization processing, and relates to the technical field of Internet of Things production control. The invention discloses a full-flow control system for galvanization processing. The full-flow control system comprises a data acquisition module, a micro-flow field observation module, a risk calculation module, a parameter decision module, a comprehensive optimization module and a data positioning module. According to the method, a physical information neural network containing electrochemical constraint and thermal-fluid conservation constraint is introduced into a CFD digital twinborn model, and assimilation is carried out on micro-flow field observation data, so that micro-flow field state and dynamic evolution prediction synchronous with a production line are obtained; on the premise of ensuring mass balance and energy balance, the physical consistency and precision of flow field reconstruction and prediction are improved, and credible flow field state representation is provided for defect risk assessment and control decision based on the micro-flow field.

The invention provides a method and a device for determining the content of organic macerals in a rock sample. The method for determining the content of the organic macerals in the rock sample comprises the following steps: collecting a plurality of images of the rock sample through a microscope; wherein the plurality of images are acquired by the microscope for multiple times; splicing the plurality of images to generate a spliced image; and determining the organic maceral content of the rock sample according to the spliced image. According to the method and the device for determining the content of the organic maceral in the rock sample, provided by the invention, manual full-vision field observation and photographing are not needed, and offline image processing can be carried out only by obtaining one or a plurality of large images, so that the time of occupying a microscope can be saved, and the efficiency can be greatly improved.

The invention relates to an aperiodic disturbance control vibration grid turbulence generation device, which comprises a vibration grid device and a flow field observation device, and is characterized in that the vibration grid device comprises a water tank frame, a water tank, a linear slide rail, a linear module, a vibration grid, a motor and a control system PLC module; the flow field observation device comprises an optical platform, an auxiliary LED lamp and a particle image velocity measurement system, wherein the particle image velocity measurement system comprises a high-speed camera, a laser and a computer. According to the invention, isotropic turbulence in a complex mode can be simulated, and the application range of equipment is expanded. According to the invention, the limitation of a vibration grating device based on periodic disturbance control is overcome, and a more flexible experiment platform is provided for turbulence mechanism research and application of the turbulence mechanism in the fields of material transportation, diffusion, sedimentation, flocculation and the like.

The invention provides a sodium ion specific fluorescence labeled transparent soil sample as well as a preparation method and application thereof, and belongs to the technical field of rock soil and geological engineering. The method comprises the following steps: firstly, sequentially carrying out hydrophilization treatment, solvent evaporation and dissolution on a sodion combined benzofuran isophthalate probe to obtain a probe mother solution; mixing the probe mother solution, a buffer solution, an inorganic sodium salt solution and a solvent to prepare a fluorescence labeling pore solution; and finally, mixing the sodium polyacrylate particles and the fluorescence labeled pore liquid, and performing vacuum saturation treatment to obtain the transparent soil sample. The transparent soil sample provided by the invention still keeps excellent optical transparency while having sodium ion specific response capability, so that a stable and reliable experimental medium is provided for in-situ, real-time and full-field observation of sodium ion migration.

The invention provides a neurology patient remote intelligent monitoring and nursing early warning device and method based on the Internet of Things, the device comprises a hardware part and a software part, the hardware part comprises a sensor module, a wireless communication module, an intelligent terminal device and a wearable device; the sensor module comprises a high-precision heart rate sensor, a blood pressure sensor, a blood oxygen saturation sensor, a brain wave sensor and an acceleration sensor and is used for collecting vital signs and behavior data of a patient in real time; the wireless communication module supports wireless communication technologies such as ZigBee, LoRa and 5G, and ensures real-time transmission of data. By arranging a hardware part, a software part, a sensor module, a wireless communication module, an intelligent terminal device and a wearable device, the problems that an existing traditional monitoring mode depends on field observation or regular inspection of medical staff, efficiency is low, and time and labor are wasted are solved. And important information is easily missed due to insufficient resources of medical staff or limitation of the activity range of the patient.

The invention discloses a compaction degree measuring and calculating method based on multi-physics field joint inversion. The method comprises the following steps: acquiring multi-physics field observation data and rock-soil compaction characteristic parameters of a to-be-detected area; establishing a mapping relationship between the moisture content and the observation data and between the dry density and the observation data by using a pre-established forward model; executing joint inversion iteration, and updating the state variable based on the observation residual error; in the iteration process, a physical feasible region is constructed by utilizing rock-soil compaction characteristics, and the physical feasible region is embedded into the inversion process as a constraint condition to constrain the value ranges of the dry density and the water content; and in response to the condition that the joint inversion iteration process meets a preset convergence condition, outputting the dry density after inversion convergence and calculating the compaction degree. According to the method, the problems that a traditional inversion solution violates the soil engineering compaction rule and cannot adapt to compaction under variable work conditions are solved, and the physical authenticity and precision of compaction quality detection are improved.

The invention relates to the technical field of frozen soil hydrothermal coupling, in particular to a frozen soil hydrothermal coupling model based on a physical information neural network, which comprises the following steps of: 1, deducing a control equation, including deducing an energy conservation equation and deducing a mass conservation equation; 2, an auxiliary equation is established; 3, initial conditions describe physical field distribution in the whole domain at the beginning of calculation, and in practical application, the initial conditions are generally determined based on field observation data or theoretical analysis; 4, describing physical field constraints on the boundary of the computational domain according to boundary conditions, wherein the boundary conditions generally comprise a Dirichlet boundary condition, a Neumann boundary condition and a mixed boundary condition; and step 5, a physical information neural network method. According to the method, efficient meshless calculation is achieved, powerful support is provided for model parameter inversion and cold region engineering real-time prediction, and the practical value and application potential of the method are remarkably improved.

The invention discloses a three-dimensional experimental device and method for measuring a gravity flow transient flow field in real time. The inflow diffusion system is composed of a water inlet hose and diffusers, diffusers of different structures are adopted for plume and density flow, and therefore uniform and stable inflow conditions are created; the terrain simulation system comprises an experiment water tank, an overflow pool and a terrain obstacle, and it is fully guaranteed that stable inflow can be supplied for a long time in the water tank with the finite length. The flow field observation system is divided into a laser surface making module, a data recording module and a structure supporting module, and quasi-three-dimensional multi-angle measurement is carried out on the flow process of plume and density flow by configuring PIV system equipment at different positions. By arranging the diffuser and combining the PIV technology with the electric sliding rail, the evolutionary process of plume / density current flowing through complex natural terrains / engineering objects in the actual situation is reproduced through simple operation, and the flowing process of snow melting plume flowing through the bottom of an iceberg can be simulated.

The invention discloses an aerodynamic noise prediction model construction method of an unsteady transient maneuvering state rotor aircraft, and belongs to the technical field of aircraft noise prediction. The problem that in the prior art, a traditional aircraft noise prediction method is difficult to achieve instantaneous efficient aerodynamic noise prediction under the maneuvering state of a rotor type aircraft is solved. The method comprises the following steps: constructing a six-degree-of-freedom linearization equation of the Updating the manipulated variable and state variable of the rotor aircraft based on a trajectory tracking control law, and outputting a maneuvering flight simulation data file; the sound pressure contribution of each sound source infinitesimal to a far-field observation point is calculated based on a Farassat 1A formula, time dimension interpolation is carried out on the far-field observation point at the observation time, integral summation is carried out on the infinitesimal sound pressure contribution at the same observation time to obtain sound pressure time calendar data of the observation point, discrete Fourier transform is carried out on the sound pressure time calendar data, and the noise characteristics of the maneuvering-state rotorcraft are obtained through analysis. The method improves the calculation efficiency of calculating the infinitesimal sound pressure contribution at the observation point time, and can be used for predicting the instantaneous noise of the aircraft.

The invention discloses a large-view-field compound eye telescopic system suitable for daytime observation, and belongs to the technical field of optical system design. The system comprises a primary mirror, a compound eye optical unit, a refraction correction mirror group unit and a photoelectric detector unit which are sequentially arranged along an optical axis. The compound eye optical unit adopts a light splitting reflection cube-corner prism structure, and divides a focal plane of a primary lens into X paths of sub-view fields; the refraction correction lens group unit comprises n correction lens groups with built-in field diaphragms; a concentric annular light barrier group is arranged on the inner wall of the primary mirror chamber. Large-view-field observation is realized through optical splicing of a compound eye structure, strong background stray light in the daytime is remarkably inhibited by utilizing a built-in view field diaphragm and combining multiple scattering absorption of a light barrier group, and the stray light coefficient of the system is lower than 1.11 * 10 <-7 >. The technical problem that an existing optical telescope cannot carry out high-contrast large-view-field observation in the daytime is solved, and all-weather monitoring of near-earth celestial bodies is achieved.

This invention relates to the field of highway slope inspection technology. Existing technologies cannot meet the actual needs of digital inspection and intelligent operation and maintenance of highways. It provides a multi-source spatiotemporal registration and positioning method and system for highway slope inspection, including multi-source joint correction of the predicted state of the inspection terminal at the current moment; constructing a near-field observation sector at the current moment; dividing the coverage area of ​​the near-field observation sector into several candidate spatial units; identifying abnormal areas and extracting their boundary range and spatial center position, and matching them with the route centerline of the current inspection section to obtain the corresponding mileage marker information; mapping the abnormal areas into standardized structured positioning results; and combining the current point cloud registration quality, point cloud overlap, satellite positioning quality, and terminal attitude stability to evaluate the reliability of the positioning results for abnormal areas. This enables the results to directly serve slope inspection documentation, maintenance and treatment assignment, and verification.

This invention belongs to the field of agricultural fungicides, and provides a fungicidal composition containing methamidophos and fluopyram and its application, wherein the mass ratio of methamidophos and fluopyram is 1:2-1:70; the fungicidal composition has excellent synergistic effects on crop diseases; it can effectively reduce the dosage of pesticides, slow down the development of pesticide resistance in diseases, reduce environmental pollution, and is safe for crops in field observations.

The invention discloses a garden planting device and method, and belongs to the technical field of garden planting. Comprising a main supporting frame, a rear wheel supporting frame, a rotating wheel and fixing blocks, the main supporting frame is fixedly connected with the rear wheel supporting frame, the rotating wheel is rotationally arranged on the rear wheel supporting frame, the multiple fixing blocks are fixedly arranged on the outer side curved surface of the rotating wheel in an equal-angle circumferential array mode, and the fixing blocks extend obliquely. A planting assembly used for sowing seeds is arranged on the rear wheel supporting frame. According to the invention, a user does not need to carry out field observation on the green lawn in the garden in real time, the labor intensity of the user is reduced, meanwhile, when the green lawn in the garden goes wrong, the message notification can be received at the first time, so that targeted maintenance operation is carried out, and the convenience of garden maintenance is further improved.

The invention discloses a hydrological parameter transplanting method, a small watershed flood forecasting method, equipment, a medium and a product, and relates to the technical field of hydrological forecasting and hydrological parameter determination. According to the method, firstly, space unit division is carried out on a research area, then a similar area is determined for each space unit, and hydrological parameters of enough first-class space units in the similar areas are determined by adopting a parameter mapping mode; according to the method, hydrological parameter transplantation is carried out based on parameter mapping and spatial interpolation modes, hydrological parameters of different space units of a small watershed are determined, and the problem that the hydrological parameters of different space units of the small watershed cannot be determined due to data scarcity and insufficient field observation is solved. The hydrological parameters are difficult to quantify accurately, and accurate determination of the hydrological parameters is realized.

An inspection apparatus according to the present disclosure includes a first optical system that illuminates a film with first light transmitted through the film and receives first observation light from a first surface side of the film, a second optical system that illuminates the film from the first surface side with second light reflected from the first surface of the film and receives second observation light from the first surface side, and a determination unit that determines whether a position of a defect of the film is a defect above the first surface of the film or a defect below the first surface based on a combination of an observation result of bright-field observation in the first optical system and an observation result of dark-field observation in the second optical system.

A metal zero-length spring gravimeter measurement system for field observation, wherein a zeroing motor is installed at the bottom of the top plate, the output shaft of the zeroing motor is connected to a zeroing pinion, the zeroing pinion is meshed with a zeroing gear, the inner ring of the zeroing gear is threadedly connected to a spring fixing tube, a metal zero-length spring is arranged in the spring fixing tube, the upper cover plate is connected to the lower cover plate by a support assembly, a locking pendulum motor is installed on the top of the upper cover plate, the locking pendulum motor is connected to a control terminal signal, the output shaft of the locking pendulum motor passes through the upper cover plate and is connected to a transmission pinion, the outer periphery of the transmission pinion is meshed with a first locking pendulum gear, the first locking pendulum gear is meshed with a second locking pendulum gear, the metal zero-length spring moves longitudinally along the zeroing tube, a magnetic steel is arranged in the metal frame, a circle of copper wire is wound around the outer side of the metal frame, and the copper wire is electrically connected to an external power supply. The metal zero-length spring of the present invention is not easily affected by vibration during field observation.

The application discloses a high-speed wind tunnel applied to three-dimensional PIV, which comprises a nozzle section and an experimental section, wherein the experimental section is provided with an experimental area capable of placing an experimental model or a real aircraft; a concave cavity is arranged on the wall surface downstream of the experimental area of the experimental section, and an observation window is arranged on the wall surface of the concave cavity and faces the experimental area. The application is applied to the field of aerodynamics, and the angle of the observation window can be flexibly adjusted according to the characteristics of the supersonic flow field. The camera lens can be arranged vertically to the observation window during flow field observation, the imaging blur problem caused by the refraction of the observation window glass is avoided, clear flow field images are ensured to be shot, and the three-dimensional velocity field can be accurately calculated.

The present invention belongs to the field of hyperspectral data processing technology, specifically to eliminate the influence of clouds in GIIRS data of a portion of the cloud field of view, realize clear-sky infrared spectrum reconstruction, and thus effectively improve data utilization. For the GIIRS cloud field observation data of the geostationary platform, by utilizing the observation data of the radiometric imager (AGRI) with higher spatial resolution on the same platform, on the basis of the traditional clear-sky correction algorithm, combined with the characteristics of GIIRS and AGRI data, a "three-step optimization" algorithm is proposed. It uses multiple time-series AGRI observation data information, comprehensively considers multiple infrared window channel information, and compares the reconstruction results of multiple auxiliary fields of view to reduce errors, thereby obtaining high-precision reconstruction results of the clear-sky infrared spectrum of the GIIRS portion of the cloud field of view, improving the utilization rate of satellite data, and further providing data support for data assimilation and meteorological analysis.

The invention discloses a parallel plate ion mobility measuring device and method for field observation. The equipment comprises a three-layer parallel flat plate ion current assembly, an electric field measuring instrument, a first direct-current power supply, a second direct-current power supply, an ampere meter and a measurement and control device, the three layers of parallel plate ion current assemblies are used for generating ions and forming a synthetic electric field; the ampere meter is used for being connected with the three-layer parallel flat plate ion current assembly and generating a current reading for indicating the density of the ion current; the electric field measuring instrument is arranged right below the three layers of parallel plate ion current assemblies and is used for generating a field intensity reading for indicating the size of a synthetic electric field; and the measurement and control device is used for executing a self-calibration program and a self-measurement program of the electric field measurement instrument so as to control the output voltage of the first direct-current power supply and the output voltage of the second direct-current power supply, obtain a current reading, obtain a field intensity reading and calculate the ion mobility. The system is high in accuracy, high in stability, convenient to use, good in portability and high in automation degree.