911 results about "Field tests" patented technology

The invention provides a geotechnical engineering earthquake sand liquefaction discrimination method and system, and relates to the technical field of geotechnical engineering, and the method comprises the steps: collecting site basic data (a site parameter table, earthquake acceleration and pore pressure time history data); establishing a preliminary numerical model and applying boundary conditions to correct the preliminary numerical model into a complete numerical model; the pore pressure ratio and the shear strain distribution are obtained through nonlinear dynamic analysis, and the liquefaction risk is comprehensively evaluated; a key soil layer observation scheme is made according to the prediction result, field verification is carried out, and a final judgment result is obtained by combining actual measurement and numerical simulation. According to the method, numerical analysis and actual measurement data are combined, the sand liquefaction risk is rapidly and accurately evaluated, and field testing and observation are guided.

A method for artificial intelligence recognition of ground penetrating radar images first obtains a noise-free high-resolution simulated ground penetrating radar image through forward simulation; obtains the ground penetrating radar field test data and determines the manual features; establishes a ground penetrating radar graph library based on the simulated ground penetrating radar image and the ground penetrating radar test image; uses a multi-layer convolutional neural network to process the measured image data of the target to determine the autonomous learning features; and finally, determines the final type and final location information of the target disease based on the manual features, the autonomous learning features, and the ground penetrating radar graph library using the committee discrimination method. The accuracy and efficiency of recognition of internal diseases in pavement structures is improved by constructing a ground penetrating radar graph library that integrates manual features, autonomous learning features, and the committee discrimination method.

The present disclosure provides a method for measuring flow velocity of multilayer groundwater using distributed optical fiber with point-source active heating, comprising: setting and optimizing field test parameters; conducting a background temperature monitoring test; performing a point-source active heating distributed temperature measurement test, including conducting multiple rounds of heating tests; denoising the obtained multi-point source thermal plume attenuation signal data of the groundwater; searching for the peak value of temperature-permeability curve based on an automatic multi-scale peak search algorithm; performing secondary processing on the peak data; estimating the groundwater flow velocity. The method of the present disclosure solves the problem that the existing groundwater flow velocity measurement technology cannot simultaneously measure multiple points and multiple layers, and it can avoid groundwater contamination during the measurement process.

The invention provides an intelligent prediction method and device for the bearing capacity of a pile foundation, and the method comprises the steps: forming an in-situ test sample based on an engineering geology in-situ test; the optimal geological parameters of the karst geology are obtained through inversion of the proxy model; and geological parameters of the field test under multiple working conditions are obtained, and a pile foundation field test sample library is formed. Obtaining pile foundation bearing performance parameters of various karst geologies under a pile foundation reduced scale model experiment to form a pile foundation reduced scale model sample library; carrying out analogue simulation on the optimal geological parameters of each karst geology to form a pile foundation analogue simulation sample library; constructing a pile foundation bearing capacity training sample library by the three sample libraries; training the pile foundation bearing capacity prediction model; and geological parameters of a construction site are input into the pile foundation bearing capacity prediction model, and the pile foundation model of the actual construction site is optimized and adjusted based on the obtained geological parameters. According to the method, data of four research paradigms are fused, and a more comprehensive and accurate intelligent prediction method for the bearing capacity of the pile foundation is constructed.

The invention discloses a spherical crown dome horizontal circumference drilling and blasting parameter model optimization construction method, and the method comprises the steps: collecting geological, crustal stress, hydrological and structural plane data, building a three-dimensional geological information model, carrying out the working condition partitioning based on a surrounding rock quality evaluation index, and constructing a parameter probability distribution model and an uncertainty boundary of each partition. Therefore, precise space description and parameter variability quantification of the spherical crown dome construction area are realized. The method comprises the following steps: establishing a three-dimensional numerical model of a cavern group, integrating blasting power, seepage and stress multi-physical field effects by adopting a finite element-discrete element coupling method, introducing a surrounding rock deterioration constitutive model considering cumulative damage and unloading aging, calibrating key parameters through an indoor test and field trial explosion, and establishing a three-dimensional model of the cavern group. And the numerical model can truly reflect the mechanical property degradation track of the surrounding rock under repeated blasting disturbance.

The invention discloses a landslide early warning method and system, and the method comprises the steps: carrying out the field testing of a sampling point through a multi-parameter soil rapid detection device, obtaining the index data of the water content, density, particle size distribution and the like of the soil, uploading the data to a cloud server in real time through a wireless transmission module, and achieving the comprehensive evaluation of the soil indexes; according to the soil evolution prediction result, combined with a preset landslide risk threshold value, the landslide risk grade is dynamically evaluated, if the predicted landslide possibility exceeds the threshold value, an early warning signal is generated, and the early warning signal is pushed to related departments and personnel in real time through a wireless transmission module; according to different geological conditions and landslide types, a plurality of soil property-environment factor coupling analysis sub-models are pre-established, and according to the geological features of the current sampling point, the optimal sub-model is dynamically selected to perform landslide risk pre-judgment, so that the applicability and accuracy of early warning are improved.

The invention discloses a conversion efficiency calculation method and system of a wave energy power generation device, and relates to the field of field test and analysis of the wave energy power generation device, and the method comprises the steps: obtaining a matching data set of a test sea area in a set time period; the matching data set comprises multiple pieces of wave observation data and the average electric power of the wave energy power generation device in the time interval of each piece of wave observation data; performing quality control on the wave observation data in the matched data set by adopting a data quality control algorithm; the angle of the head wave direction of the wave energy power generation device in the set time period is obtained, and a target data set is constructed according to the angle of the head wave direction of the wave energy power generation device in the set time period and the matched data set after quality control; and calculating the conversion efficiency of the wave energy power generation device in the time interval of each piece of wave observation data according to the target data set. The accuracy of the calculation result of the conversion efficiency of the wave power generation device during the whole test period is improved.

The invention discloses a grouting parameter intelligent feedback method based on rock mass groutability evaluation, which comprises the following steps: collecting geological condition data, rock mass quality data, field test data and grouting process data, and constructing a rock mass groutability grading data set; an SMOTE algorithm is adopted to process data imbalance, input indexes are screened through Pearson correlation analysis, and data are normalized through deviation standardization; an XGBoost classification model is constructed, hyper-parameters are optimized through grid search, the model is trained through K-fold cross validation, and the rock mass groutability grade is evaluated; constructing an XGBoost regression model by taking a rock mass groutability grade, grouting construction data and monitoring data as input, and predicting the maximum value and the minimum value of grouting pressure and slurry density by using an optimal model; and generating a grouting parameter interval according to the predicted maximum value and minimum value, and dynamically feeding back to the grouting equipment to regulate and control parameters. According to the method, scientificity and accuracy of rock mass groutability evaluation and grouting parameter regulation and control can be effectively improved.

The invention discloses an intelligent injection molding product quality prediction method, which comprises the steps of collecting product structure information, mold parameters and injection molding equipment operation parameters, and constructing a scientific mold testing process window based on simulation analysis; designing an orthogonal experiment scheme to generate a simulation data set, and forming a multi-source data training sample in combination with field test model data; training a quality prediction model by using a distributed gradient boosting tree model, inputting process parameters, and outputting quality indexes such as product gram weight, volume shrinkage and buckling deformation; the model interpretability is realized through a shop value analysis method, and the influence weight of the process parameters on the quality indexes is evaluated; the model is deployed in a production control system or a cloud platform, the product quality is predicted in real time, a dynamic feedback mechanism is established, and when the error between actual detection data and a predicted value exceeds a threshold value, model retraining and parameter correction are automatically triggered to form closed-loop control. The method effectively improves the accuracy, transparency and engineering adaptability of quality prediction of the injection molding product, and can be popularized.

The invention belongs to the technical field of agricultural information, and discloses a rape variety environmental adaptability evaluation system based on machine learning. The system is composed of a data acquisition standardization unit, a regional environment feature modeling unit, a variety phenotype and pedigree association unit, a feature screening and model training unit, a regional adaptability scoring and decision-making unit, a dynamic learning and evolution updating unit and an evaluation visualization and variety recommendation unit. By performing standardization processing on multi-source data, format and dimension differences are eliminated, and a high-quality data foundation is laid for subsequent analysis. Fusing environment and variety bilateral characteristics, and enabling the model to capture environment influence and variety heredity characteristics at the same time. Advanced methods such as ensemble learning and a time sequence neural network are adopted, and the complex relation is accurately mined. Compared with a traditional field test and the prior art, errors are greatly reduced, the adaptation degree of the variety in different areas is more accurately judged, a scientific basis is provided for planting recommendation, and the yield and quality of the oilseed rape are improved.

The invention discloses a primary and secondary collaborative planning method based on a novel power distribution system, and relates to the technical field of power system optimization, and the method comprises the following specific steps: constructing a power distribution network model and fault feature analysis, designing an adaptive protection mechanism, realizing a rapid fault processing mechanism, and performing primary and secondary system collaborative planning. And implementing and verifying: implementing a planning method in the power distribution network, installing and debugging related equipment, carrying out field test, and verifying the effectiveness of an adaptive protection mechanism and a fault rapid processing mechanism, the running state of the power distribution network is monitored in real time, and the protection constant value is automatically adjusted according to the monitored fault characteristic parameters, so that the reliability of the power distribution network is improved. Therefore, the adaptive capacity of the system to a complex and changeable operation environment is remarkably improved, the dynamic adjustment mechanism can quickly respond to dynamic factors of new energy output fluctuation and load change, it is ensured that a protection strategy is always matched with the operation state of the system, and the problem of protection maloperation or operation refusal caused by rigid setting of a fixed value is effectively prevented.

The invention discloses a hydraulic characteristic simulation and evaluation method and system for a rotation irrigation unit pipe network of a drip irrigation system, and relates to the field of agricultural irrigation, and the method comprises the steps: obtaining the design and operation data of a tree-shaped pipe network of each irrigation cell, and the data of an irrigation emitter; based on the design and operation data, drawing a plane layout diagram of a rotation irrigation unit annular pipe network of each irrigation cell, and establishing a pipe network hydraulic model; according to the design and operation data and the emitter data, hydraulic information parameters of the pipe network hydraulic model are determined, and model simulation is carried out; performing model calibration according to a model simulation result and a field test result; and according to a simulation result of the pipe network hydraulic model after model calibration, evaluating an irrigation emitter flow simulation effect, and evaluating an annular pipe network optimization effect. The invention provides a relatively efficient drip irrigation pipe network optimization design method and evaluation method, and a basis is provided for transformation and upgrading of a large-scale drip irrigation system.

The invention relates to the technical field of laser transmission characteristic testing, in particular to a medium-wave infrared laser long-distance transmission attenuation characteristic external field testing method and device. The method is an indirect measurement method, a diffuse reflection plate is set up at a designated position of a transmission path, laser reaching the diffuse reflection plate is quantitatively measured through a detector, in combination with a bidirectional reflection distribution function of the diffuse reflection plate, the target reaching power of the laser transmitted through the long-distance atmosphere is obtained, and the target reaching power is calculated by comparing the target reaching power with the laser output power of a transmitting end. The laser long-distance transmission power attenuation characteristic can be obtained, and the problems that in current laser atmospheric transmission attenuation characteristic measurement, a laser radar does not have a medium-wave infrared measurement method, and the power of a specified position of a transmission path cannot be directly received and measured through a detector due to the fact that the size of a light spot is too large after long-distance transmission in direct measurement are solved. The measuring device is simple in structure and can support indirect measurement to obtain the long-distance transmission power attenuation characteristics of the medium-wave infrared laser.

The invention discloses a thermal tracing test device and method for determining the comprehensive hydrogeological condition of an aquifer, and the device comprises a water storage system, a medium groove, a heating system, and a distributed optical fiber data collection system. The device is simple in structure and intelligent and convenient to operate, instantaneous / continuous linear heat source excitation can be achieved through the heating system, and the water pressure and temperature change conditions of all positions are monitored in real time through the distributed optical fiber data acquisition system; the comprehensive hydrogeological parameters such as the flow velocity, the flow direction, the permeability coefficient, the thermal diffusion coefficient, the thermal capacity and the heat conductivity coefficient of underground water are studied, the heating system and the distributed optical fiber data acquisition system can be used for indoor tests and field tests, operation is easy and convenient, data precision is high, and practicability is high.

The invention relates to a roadbed compaction quality monitoring, management and maintenance method and system based on virtual and real index collaboration. The method comprises the following steps: step 1, establishing an indoor compaction test for reproducing on-site roadbed compaction conditions, and establishing a data set of the indoor test; 2, implementing a field test on roadbed pressure, and establishing a data set of the field test; 3, building a roadbed compaction quality prediction model based on virtual and real data collaborative training; and 4, carrying out construction management and control application on the roadbed compaction quality prediction model based on virtual and real index collaborative prediction. According to the method, the influence of roadbed filler parameters, road roller working parameters and external environment parameters of roadbed compaction on the compaction quality is fully considered, multiple virtual-real indexes cooperate with one another to establish an artificial neural network compaction quality prediction model of the roadbed compaction quality, and the model is optimized and improved while being migrated to engineering practical application. And real-time accurate monitoring, management and maintenance of the compaction quality are realized in the on-site roadbed compaction process.

The invention provides an electromagnetic compatibility design method and device based on a vehicle-mounted audio system. The method comprises the following steps: determining a target level of electromagnetic compatibility; performing risk assessment on the device in the drawing to obtain a risk assessment result; selecting clock frequency points of signal radiation from the devices meeting the design requirements; performing simulation verification on the vehicle-mounted audio system, and judging whether the vehicle-mounted audio system reaches a target level or not; if not, optimization design is carried out; if yes, carrying out near-field testing on the whole machine; judging whether the near-field test reaches a target level or not; if not, optimization design is carried out; if yes, performing a far-field test on the whole machine; judging whether the far-field test reaches a target level or not; if not, optimization design is carried out; if yes, ending; through simulation optimization, it is ensured that the electromagnetic compatibility of the whole machine design can reach an expected target level, and therefore the quality and reliability of products are remarkably improved; the research and development period can be shortened, and the research and development cost is reduced.

The invention relates to the technical field of motor testing, in particular to a motor stator temperature field testing and analyzing method, device and system, and the method comprises the steps: obtaining a plurality of first temperature values and second temperature values under a preset testing condition, the second temperature value is collected by a second thermocouple sensor, the first thermocouple sensor is arranged in a coil of a stator core of the motor, the second thermocouple sensor is arranged in a groove of the stator core, and the groove is distributed on the periphery of the stator core; obtaining fitting data of the stator temperature field based on the first temperature value and the second temperature value; on the basis of fitting data, abnormal temperature point identification and temperature field future change prediction are carried out; according to the method, the actual measurement of the internal temperature and the peripheral temperature of the stator is realized, and compared with temperature field data simulation, the precision of the fitting data of the temperature field obtained by the method is relatively high, and the improvement of the precision of subsequent data analysis is facilitated.

The invention provides a pilot operated safety valve with filtering and field testing functions, which relates to the technical field of pressure relief valves, comprises a pilot operated valve body, a main valve and a valve core, and is provided with a filtering mechanism and a flow testing mechanism. The filtering mechanism comprises a filter screen assembly and a sealing assembly movably installed in the filter screen assembly, an insertion hole communicated with the interior is formed in the side wall of the main valve and used for embedding the filter screen assembly, and the sealing assembly is automatically switched to a first state when liquid flows, blocks a gap between the filter screen assembly and the insertion hole and starts the flow testing mechanism; when the liquid stops flowing, the second state is switched, and blockage is relieved so that the filter screen assembly can be taken out and the flow testing mechanism can be closed. The flow testing mechanism is located downstream of the filter screen assembly and used for detecting the liquid flow. According to the design, integration of the filtering function and the flow testing function is achieved, operation, maintenance and testing are convenient, the sealing performance and the operation efficiency of the system are improved, and the system is suitable for fluid control and monitoring under complex working conditions.

The invention relates to a lane keeping auxiliary system operation comfort evaluation method based on machine learning, and the method comprises the steps: carrying out a field test through employing an automatic driving vehicle equipped with a lane keeping auxiliary system, and obtaining weather environment information, road geometry and traffic marking information, driving behavior information and a driver comfort test result; screening the obtained information by using a recursive feature elimination algorithm to serve as a system operation comfort feature parameter, and determining a comfort threshold value by using a receiver operation feature curve analysis method; using weather environment information and road geometry and traffic marking information as input information, and adopting a machine learning method to predict driving behavior information; and based on a driving behavior information prediction result, a comfort evaluation model is constructed by adopting a machine learning method so as to evaluate the operation comfort of the lane keeping auxiliary system. The method can fully consider the real world conditions during the operation of the lane keeping auxiliary system, and effectively improves the accuracy of the evaluation result of the operation comfort of the lane keeping auxiliary system.

The invention provides an OFDR-based rock surface strain field test method and system, and particularly relates to the technical field of rock dynamic failure monitoring, the method comprises the following steps: winding a distributed optical fiber on the outer surface of a rock sample to obtain an annular optical fiber and a spiral optical fiber, and applying a compression force to the rock sample to obtain a strain field of the rock surface strain field; according to the optical signals in the circumferential optical fiber and the spiral optical fiber, circumferential strain distribution and axial strain distribution are obtained through calculation, and the method solves the problem that it is difficult to dynamically monitor the surface strain change of the test piece in the failure deformation process in real time with high precision. The effect of real-time dynamic high-precision monitoring of the surface strain of the test piece in the damage deformation process of the test piece is achieved.

A test device tests conditions associated with a fronthaul in an Open Radio Access Network (O-RAN). The test device can field test an O-RAN radio unit (O-RU) installed at a cell site by emulating an O-RAN distributed unit (O-DU) in the O-RAN connected to the O-RU via the fronthaul of the O-RAN. The testing includes testing connectivity of the O-RU to the fronthaul. The testing includes executing managing plane (M-plane) and synchronization plane (S-plane) messaging to test management session establishment, device setting testing, and master clock synchronization testing. Additionally, optical insertion loss in the fronthaul and frequency and power of signals transmitted from the O-RU can be tested.

The invention provides an SVG controller modeling analysis method based on field experiment data, and relates to the technical field of electric power grids. According to the method, the high-low penetration fault test is carried out on the SVG, the field experiment data is obtained, the calculation data of the transient model of the SVG under different model parameters are combined, the least square method is adopted to carry out parameter identification, and the optimal model parameters of the transient model of the SVG controller are obtained. The process avoids modeling of complex topology in the SVG and laboratory communication protocol debugging, is suitable for testing of SVGs of various models, and is high in field test result accuracy, simple in wiring and extremely low in risk. A field test result can truly reflect transient response characteristics of station-level current and reactive power, and a modeling path based on the field test is opened. The SVG control characteristic extraction efficiency is improved, the model precision and modeling efficiency of the complex topology SVG are improved, and therefore the analysis efficiency of the SVG analysis process is improved.

The invention discloses a refined grain crop yield prediction method and system, belongs to the technical field of agricultural yield prediction, and solves the problems that the prediction precision is low and day-by-day prediction and overfitting cannot be realized when the crop yield of a small plot scale is predicted. The method comprises the following steps: obtaining food crop data, wherein the food crop data comprises meteorological data and crop emergence period data; dividing the prediction area into a plurality of parameter adjustment areas, and establishing a simulation algorithm based on a WOFOST crop mechanism model for each parameter adjustment area; performing day-by-day simulation by using a WOFOST-based crop mechanism model simulation algorithm to obtain a crop development process, a leaf weight, a stem weight, an ear weight, an overground part dry matter weight and a leaf area index; and taking the output data based on the WOFOST crop mechanism model simulation algorithm, the meteorological elements, the statistical yield data, the field test data and the agrometeorological observation data as the input of an LSTM algorithm, and obtaining a prediction result of the yield of the food crops. The method is suitable for real-time and refined prediction of the crop yield.

The invention belongs to the technical field of agricultural biology, and relates to a rice high-yield salt-tolerant molecular marker and application thereof. The rice high-yield salt-tolerant molecular marker is located at the 615th and 560th sites of chromosome 6 of a rice reference genome IRGSP1.0, and the polymorphic site is G / A. The invention further discloses a preparation method of the rice high-yield salt-tolerant molecular marker. The high-yield and salt-tolerant characteristics of the germplasm carrying the A nucleotide allelic variation at the site are obviously lower than those of the germplasm carrying the G nucleotide allelic variation, specifically, the yield of the GG genotype is the highest, the yield of the GA genotype is the middle, and the yield of the AA genotype is the lowest. By utilizing the molecular marker and the corresponding identification method, the genotype can be accurately and rapidly identified in the accurate design of the high-yield salt-tolerant rice, the phenotype identification cost of a field test in the later period is reduced, and the application of an accurate design technology of the rice in breeding is promoted.

The invention discloses a rock mass elastic modulus probability estimation method, which comprises the following steps: S1, acquiring a compression wave velocity Vp of a rock on the basis of field test investigation and statistics for a to-be-estimated hole section area of a rock mass mechanical parameter; s2, determining priori knowledge about the rock elasticity modulus; s3, constructing a Bayesian calculation framework; s4, using an adaptive MH-MCMC algorithm to iterate relevant parameters in the relation equation under a Bayesian calculation framework, generating posterior probability samples corresponding to the rock elasticity moduli, and determining probability distribution of the rock elasticity moduli; and S5, determining the value of the elastic modulus of the actual engineering rock mass based on the H-B criterion, and obtaining the probability distribution of the on-site rock mass parameters. According to the method provided by the invention, the probability range of the rock mass mechanical parameters can be efficiently estimated, the method is used for guiding the formulation of solutions considering various conditions during actual construction, and the method has better economic benefits and has important guiding significance for engineering practice.

The utility model provides a test support device mass balancing driving system and a flow field test system. The test support device mass balancing driving system comprises an oil transportation header pipe, two oil transportation branch pipes and an oil return header pipe, each oil conveying branch pipe is connected with the oil conveying main pipe through a first stop valve, and a second energy accumulator is connected to each oil conveying branch pipe; outlets of the two oil conveying branch pipes are respectively communicated with two oil cavities of the hydraulic cylinder; one oil conveying branch pipe is connected with an overflow valve, the overflow valve is connected with the oil return header pipe through a first oil return branch pipe, the other oil conveying branch pipe is connected with the oil return header pipe through a second oil return branch pipe, and a second stop valve is arranged on the second oil return branch pipe. The balancing of the mass of the test model supporting part in the sinking and floating movement process of the flow field test can be realized, and the mass of the test model supporting part does not influence the model test. In addition, by adjusting the pressure of the balance energy accumulator, namely adjusting the pressure of the second energy accumulator, the frequency of balancing motion can be achieved, and broadband quality balancing from low frequency to high frequency can be achieved.

The invention discloses a power device for penetration sounding and a soil body three-dimensional deformation field testing device in the technical field of indoor calibration devices, the power device for penetration sounding comprises a speed measuring instrument, a transmitting tube and an adapter which are sequentially connected along the same axis, and the side face of the adapter is sequentially connected with a first electromagnetic valve, a small air chamber, a second electromagnetic valve and an air source. The air chamber is further provided with a pressure sensor used for detecting the air pressure in the air chamber. One side, far away from the launching tube, of the adapter is provided with a bomb loading port used for loading a penetrometer into the launching tube, and the bomb loading port is connected with a plug used for plugging the bomb loading port; a loading fixing piece for fixing the penetrometer is arranged in the adapter or the launching tube so as to prevent the penetrometer from freely falling in the loading process; the minimum variable quantity of the pressure in the air chamber can be reduced, the incidence speed of the penetrometer can be changed in a small range, and the situation that the penetrometer enters the soil tank at different speeds in the actual environment is accurately simulated.

The invention discloses a proportioning optimization method for efficiently balancing a chemical oil displacement system. The proportioning optimization method comprises the following steps: S1, collecting and sorting experiment and field data of the existing chemical oil displacement system; the oil displacement effect can be effectively improved by continuously optimizing the ratio of the chemical agents through experiments and numerical simulation, so that the recovery efficiency of an oil field is improved, the oil-water interface characteristics can be improved, the fluid viscosity can be reduced, the oil fluidity can be improved through the reasonable ratio of the chemical agents, and by analyzing the cost benefits of different ratios, the oil displacement effect can be effectively improved. The chemical agent combination with higher economical efficiency can be selected, the expenditure in the chemical oil displacement process is reduced, the oil displacement effect and cost are comprehensively considered, the resource utilization efficiency of the chemical oil displacement system is improved by optimizing the proportion, and it can be ensured that the selected proportion is not only theoretically effective but also theoretically effective through laboratory verification and on-site small-scale tests. And the method also has practical significance in practical application.

The invention discloses a follow-up PIV boundary layer flow field test system and test method based on electrolytic hydrogen bubbles. The follow-up PIV boundary layer flow field test system comprises an integrated optical measurement module and a tracer particle generation module, the optical measurement module is arranged in the UUV and comprises a laser transmitter assembly, a sapphire prism and two imaging cameras which are symmetrically arranged, and laser sheet light forms a sheet light area on the outer surface of the UUV after being refracted by the sapphire prism; the tracer particle generation module comprises a cathode, an anode and a power supply unit, the cathode is a platinum wire array composed of a plurality of platinum wires arranged in the axial direction of the UUV, and the platinum wires are located at different heights away from the wall face of the UUV; the power supply unit selectively electrifies the platinum wire, independently adjusts the voltage, controls the number and frequency of generated hydrogen bubbles, and achieves the synchronous measurement of flow field information at different thickness positions of a boundary layer. According to the invention, boundary layer flow field in-situ follow-up measurement and synchronous fine measurement of different thickness positions under the condition of not changing the UUV shape are realized, and the device has the advantages of high integration level, small flow field disturbance, high measurement efficiency and the like.

The invention belongs to the technical field of geotechnical engineering field test, and particularly relates to a shallow silty clay stratum classification method based on a CPTU field penetration test, which comprises the following steps: utilizing the CPTU field penetration test, correcting a conical tip resistance model and combining a normalized friction ratio model; the vertical stress of the overlying soil layer, the effective vertical stress of the overlying soil layer and the atmospheric pressure are introduced, and a normalized conical tip resistance model is obtained; then, based on boundary conditions such as a soil body type index and silty clay stratum thickness, an existing correction coefficient is optimized, and the normalized conical tip resistance model is further corrected; and finally, substituting the normalized friction ratio model and the corrected normalized conical tip resistance model into the soil body type index model to obtain a corrected soil body type index model for dividing the shallow soil body. According to the scheme, the method can more accurately meet the requirement for soil body classification, can meet the requirement for distinguishing silty clay, silty soil and silty sand, and has the advantages of being rapid, simple, high in test result reliability and the like.