240 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 relates to the technical field of wetland ecosystem soil carbon sequestration capability, in particular to a seasonal waterlogged wetland soil carbon estimation and dynamic monitoring method, which comprises the following steps of: selecting a sampling zone and a quadrat according to an equal-elevation water level gradient and a vegetation type; an optimal remote sensing estimation carbon model is determined through remote sensing image interpretation and screening of characteristic factors such as image waveband reflectivity, vegetation indexes, principal component characteristics and single-waveband textures, and soil organic carbon spatial distribution characteristics are analyzed through remote sensing inversion and GIS interpolation; constructing a Wetland-DNDC wetland carbon dynamic simulation model based on a DNDC model to predict wetland long-term carbon dynamic change and greenhouse gas emission; the invention provides a method for simulating carbon reserves and carbon dynamic monitoring based on field investigation and coupling a 3S technology with a Wetland-DNDC model. Compared with a traditional field observation method, the method has obvious technical and cost advantages, and can realize the technical advantages of spatial analysis and long-time sequence monitoring. The research method is suitable for a wetland ecosystem with seasonal hydrological characteristic changes.

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 design method and system of an earthquake geoelectric field observation device, and relates to the technical field of earthquake monitoring, firstly, through a scientific pole arrangement mode and calculation of natural potential difference, electric field changes before and after an earthquake can be effectively monitored and described, and accurate and reliable data support is provided. And secondly, the layout in eight directions shaped like the Chinese character'mi 'and a multi-electrode connection form are adopted, so that the flexibility and adaptability of the observation system are enhanced, and the requirements of different terrains and environments are met. And meanwhile, a measuring line orientation selection and electrode stability judgment mechanism is added in the design, so that the reliability and the precision of data are further improved. Besides, the system is convenient to maintain and upgrade, a good monitoring effect can be provided in practical application, and an effective technical guarantee is provided for seismic research and monitoring forecast.

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.

The present invention discloses a method for assessing nitrogen emissions from farmland soil at a regional scale based on transfer learning, the method comprising: obtaining existing farmland soil nitrogen, nitric oxide and nitrous oxide data, and constructing an emission database; establishing a coupled domain adaptive and random forest regression model based on the data in the emission database; adjusting the parameters of the random forest model using farmland soil nitrogen emission observation data, and optimizing the random forest model; using the optimized model to perform global farmland emission prediction on farmland soil nitrogen data, and obtaining a regional scale farmland soil nitrogen emission assessment result. The present invention uses field measured data of nitrous oxide and nitric oxide, which have the same production pathway as nitrogen, to construct a random forest model, and based on transfer learning technology and ideas, uses limited nitrogen field observation data to calibrate the constructed model to meet the needs of large-scale assessment of farmland soil nitrogen emissions, thereby achieving farmland soil nitrogen emission assessment.

The invention provides a speed field and temperature field synchronous measurement method based on temperature-sensitive phosphorescent particles, and relates to the technical field of flow field observation.The method comprises the steps that the service life of the temperature-sensitive phosphorescent particles is measured, and a service life-temperature curve is obtained; obtaining a time sequence image of the temperature-sensitive phosphorescent particles; performing three-view separation processing on the time sequence image to obtain a processed image; performing three-dimensional reconstruction and trajectory fitting operation on the processed image to obtain a three-dimensional velocity field; acquiring a red total-resolution image of the temperature-sensitive phosphorescent particles irradiated by the light source; calculating the temperature-sensitive phosphorescent particle intensity of the red full-resolution image, and obtaining the self-luminous lifetime through the temperature-sensitive phosphorescent particle intensity; a three-dimensional temperature field is obtained through the service life-temperature curve and the self-luminous service life; and fusing the three-dimensional velocity field and the three-dimensional temperature field to obtain a three-dimensional velocity-temperature field. According to the method, the stability of reconstructing the three-dimensional velocity field and the precision of temperature measurement are improved through the three-color mask single-color camera and the service life method of the temperature-sensitive phosphorescent particles.

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.

A metal zero-length spring gravimeter measuring system applied to field observation is characterized in that a zero-setting motor is mounted at the bottom of a top plate, an output shaft of the zero-setting motor is connected with a zero-setting pinion, the zero-setting pinion is meshed with a zero-setting bull gear, an inner ring of the zero-setting bull gear is in threaded connection with a spring fixing cylinder, a metal zero-length spring is arranged in the spring fixing cylinder, and the zero-length spring is arranged in the spring fixing cylinder. The upper cover plate and the lower cover plate are connected through a supporting assembly, the top of the upper cover plate is provided with a pendulum locking motor, the pendulum locking motor is in signal connection with a control terminal, an output shaft of the pendulum locking motor penetrates through the upper cover plate and then is in transmission connection with a transmission pinion, and the outer side periphery of the transmission pinion is meshed with a first pendulum locking gear. The first pendulum locking gear is meshed with the second pendulum locking gear, the metal zero-length spring longitudinally moves along the zero setting pipe, magnetic steel is arranged in the metal frame, a circle of copper wire is wound on the outer side of the metal frame, and the copper wire is electrically connected with an external power source. The metal zero-length spring is not prone to being affected by vibration during field observation.

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 discloses a corrosion display method of a TA22 titanium alloy grain structure. The method comprises the following steps: 1, machining a TA22 titanium alloy sample to form a microscopic structure observation plane, and grinding and washing the microscopic structure observation plane; 2, mechanical polishing is conducted till the surface is flat and bright and free of scratches and dragging; 3, anodic oxidation coating treatment; 4, immersing into an etchant solution for etching; and 5, placing under a metallographic microscope, and observing the metallographic microstructure in a way of transparent field observation. According to the method, the TA22 titanium alloy is subjected to anodic oxidation film coating and then subjected to erosion film removal, and a method for judging the grain size by observing different bright and dark contrast in a metallographic structure in a polarized field after film coating is abandoned; according to the method, the grain boundary structure in the TA22 titanium alloy metallographic structure can be clearly, accurately and intuitively observed by directly adopting a transparent field under the metallographic microscope, a polarized light view field does not need to be switched, the equipment requirement on the metallographic microscope is greatly reduced, and the method is easy to operate and suitable for popularization and application.

The invention discloses a time sequence change extraction and mutation detection method for a water area of a reservoir in a plain farmland area. Acquiring a spatial position and a historical maximum water area range of the target reservoir; preprocessing the Sentinel-1 radar image covering the maximum water area of the reservoir and the surrounding land area, and then carrying out water body crude extraction; removing farmland elements by using optical land utilization data matched with the radar image, and removing mountain shadows; abnormal values are removed through sliding window detection, intra-month mean value synthesis is carried out on non-abnormal values, and a monthly water body area time sequence of the reservoir is obtained; and performing mutation detection by using a PELT algorithm, and identifying a mutation time point of water body change. The method does not depend on field observation data, efficiently monitors the water body area change of the reservoir in the plain farmland area, analyzes the response characteristics of extreme events, adapts to a complex environment, timely identifies the water body area sudden change time point, contributes to water resource management and protection, and ensures the safety of regional drinking water resources.

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 belongs to the technical field of coordinated operation of new energy and an energy storage system, particularly relates to a polar region field observation station two-stage distribution robust optimization method considering wind and light uncertainty, and solves the technical problem of how to realize coordinated operation of the new energy and the energy storage system through the two-stage distribution robust optimization method under an extreme climate condition. Based on thermal dynamic characteristics of a polar field observation station building and adjustability of the equipment operation environment temperature, an observation station model considering the equipment operation environment temperature is constructed, and the observation station model aims at minimizing carbon emission; secondly, considering the uncertainty of wind and light output and outdoor temperature, providing a polar region field observation station two-stage distribution robust optimization method considering the wind and light uncertainty, and flexibly adjusting and optimizing the conservative degree by setting uncertainty adjustment parameters; in addition, a hydrogen energy recovery model is added in research, and the comprehensive energy utilization rate of the observation station is further improved. Then, Camp is adopted; and the optimal solution of the original problem is obtained through CG algorithm iteration solution.

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 utility model provides an ultra-precision polishing micro-flow field observation device, and belongs to the technical field of precision polishing. The device solves the problem of how to accurately control the flow rate of the polishing solution and ensure that the measurement result is more accurate at the same time. The ultra-precision polishing micro-flow field observation device comprises a die body with a flow channel inside, a micro-flow pump, a CCD camera, a liquid containing box and a fixing frame, the liquid containing box is connected with an inlet of the flow channel through a pipeline and connected with the micro-flow pump through a pipeline, the die body comprises a lower die plate provided with at least one strip-shaped groove and an upper die plate made of transparent materials, and the upper die plate is connected with the micro-flow pump through a pipeline. The upper mold plate and the lower mold plate are detachably connected so that a runner can be defined between the outer wall of the upper mold plate and the groove wall of the strip-shaped groove, the fixing frame is located on one side of the mold body, a carrier plate capable of sliding in the vertical direction and the horizontal direction is arranged on the fixing frame, and the CCD camera is fixed to the side face of the carrier plate. The ultra-precision polishing micro-flow field observation device can accurately control the flow rate of the polishing solution, and meanwhile it is guaranteed that the measurement result is more accurate.

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 chicken identification method and device based on a small sample, a storage medium and electronic equipment, and is applied to the technical field of image processing, and the method comprises the steps: collecting a chicken monitoring video of a breeding area through shooting equipment; processing the chicken monitoring video to obtain a plurality of monitoring pictures; inputting the plurality of monitoring pictures into a pre-trained recognition model, so that a chicken identity recognition model and a chicken behavior recognition model in the recognition model perform recognition processing on each monitoring picture to obtain recognition information, output by the recognition model, of each chicken in the breeding area, the identification information comprises chicken identity identification information and behavior identification information; wherein a chicken identity recognition model and a chicken behavior recognition model in the recognition model are both constructed based on a meta-learning detector framework in which a deformable detector is introduced. The recognition model is used for collecting the recognition information including the behavior data of the chicken, manual field observation is not needed, and the accuracy of the collected behavior data of the chicken is improved.

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.