194 results about "Sediment concentration" patented technology

The invention discloses a dredge pump control system and method for river regulation, and relates to the technical field of dredge pump control. The dredge pump control system comprises a sensing module, a centralized control module, an energy-saving execution module and a control parameter recording module; the sensing module is arranged on a multi-element sensor at a key part of a dredge pump for acquiring data, and the data is pre-processed by a microprocessor and then transmitted to the centralized control module at a high speed by a wireless transmission module, so that an accurate basis is provided for system control; according to the invention, by integrating multiple sensors and an advanced control algorithm, the dredging efficiency and accuracy of the dredge pump of the dredger are obviously improved; the sensing module can monitor key parameters of the dredge pump in real time, such as suction pressure, discharge flow, pump shaft temperature and sediment concentration, and it is ensured that the running state of the dredge pump is comprehensively known; and the centralized control module dynamically optimizes a control sequence by using a model predictive control and fuzzy logic control algorithm so as to adapt to variable working conditions.

The invention discloses an amphibious unmanned aerial vehicle riverway sediment concentration real-time monitoring method based on underwater light field imaging and cross-modal fusion, and relates to the technical field of riverway sediment monitoring. Comprising the following steps: acquiring aerial multispectral data and preprocessing the aerial multispectral data; an integrated polarized light field camera is carried on an amphibious unmanned aerial vehicle to capture underwater light field data, and underwater three-dimensional light field information is reconstructed and sediment scattering characteristics are extracted through an optical model and a lightweight deep learning network; the air multispectral data and sediment scattering characteristics are fused through space-time alignment and an attention mechanism, a sediment concentration prediction model is generated, and then a spatial distribution diagram of the river sediment concentration is output; and carrying out real-time monitoring and early warning on the river sediment concentration according to the spatial distribution diagram of the river sediment concentration through edge calculation and cloud collaboration architecture. The method is combined with an advanced deep learning algorithm, high-resolution silt concentration inversion can be realized, and the method has real-time performance and adapts to a complex water body environment.

The invention discloses a river model multi-data processing analysis method and system, and relates to the technical field of hydraulic engineering, and the method comprises the steps: extracting a motion feature vector from a digital twin model, and carrying out the preprocessing to generate a standard river motion data set; according to the method, the sediment space distribution concentration Nsc (x, y, z, t) in a three-dimensional coordinate grid is calculated through a standardized data set, and the change trend of the sediment space distribution concentration Nsc (x, y, z, t) along with time is evaluated. When the sediment space distribution concentration Nsc (x, y, z, t) is larger than 0, highlighting marking is conducted on the abnormal area through a visual interface; when the sediment space distribution concentration Nsc (x, y, z, t) is less than or equal to 0, the sediment concentration is normal. For an abnormal area, the method further calculates the sediment conveying capacity Qs and the sediment deposition rate S, accurately predicts the moving path, the sediment deposition area and the sediment deposition speed of the sediment, dynamically analyzes the sediment movement condition of the river, and can track the sediment change trend in real time in a complex dynamic environment.

The invention provides an optical complex water body suspended sediment monitoring method based on man-machine cooperation, and belongs to the technical field of remote sensing water environment monitoring. The method comprises the following steps: acquiring a multispectral remote sensing image of a target area, preprocessing the multispectral remote sensing image, and performing space-time fusion to obtain a spectral data set with high space-time resolution; carrying out manual labeling on the spectrum data set, constructing a suspended sediment concentration classification data set, and carrying out synthesis expansion on a minority class of samples to generate an equalization training set; training a suspended sediment concentration inversion model by using the equalized training set to obtain an initial suspended sediment concentration predicted value, and dynamically optimizing the spectral feature weight and the classification boundary of the suspended sediment concentration inversion model based on expert knowledge; and locally correcting the initial suspended sediment concentration predicted value and diffusing the initial suspended sediment concentration predicted value to a global range based on a hydrodynamic law and a space consistency constraint to obtain a global suspended sediment concentration predicted value. The method combines remote sensing image analysis, machine learning and expert knowledge to realize high-precision inversion of SSC.

The invention relates to the crossing field of hydraulic engineering hydrological monitoring technology and machine learning prediction technology, discloses a sediment concentration prediction method based on deep learning, and aims to solve the problems that in existing sediment concentration prediction, hyper-parameter manual tuning is low in efficiency, key feature attention is insufficient, local and time sequence information is difficult to consider by a single model and the like. Accurate prediction is realized through five core modules: a data preprocessing module performs missing value filling, abnormal value processing and derivative feature generation on hydrological data; the feature selection module screens key features based on mutual information; the time sequence construction module generates time sequence data through a sliding window; the hyper-parameter automatic optimization module adopts Bayesian optimization iteration to obtain an optimal hyper-parameter; the CNN-LSTM-attention prediction module fuses CNN local feature extraction, bidirectional LSTM time sequence dependence capture and multi-head self-attention mechanism key feature focusing capability, is suitable for scenes such as river channels and channels, and provides efficient decision support for hydrological regulation and control.

The invention provides a coastal estuary suspended sediment drift prediction method, device and equipment, and relates to the technical field of target tracking, and the method comprises the steps: obtaining a sediment image of a target monitoring area through employing an unmanned plane to carry a synthetic aperture radar; preprocessing the sediment image, and extracting sediment feature information from the preprocessed sediment image; the sediment characteristic information comprises sediment distribution information, sediment concentration, sediment particle size, sediment drift speed, longitude and latitude of sediment diffusion range, sediment shape and sediment surface area; training a preset sediment drift prediction model based on the sediment characteristic information in a preset period, determining a wind power factor and an ocean current factor which influence sediment drift, and obtaining a target sediment drift prediction model; and inputting the sediment characteristic information at the current moment into the target sediment drift prediction model to obtain sediment drift prediction information. According to the method, airborne real-time monitoring and a coastal estuary sediment prediction model are combined, and the precision of sediment drift prediction is improved.

The invention relates to the technical field of suspended sediment monitoring, in particular to a suspended sediment monitoring method and system based on a remote sensing technology. Comprising a concentration inversion module, a model establishment module, a data processing module, a remote sensing data acquisition module, an alarm module and a control platform, the concentration inversion module comprises an inversion calculation unit, a result output unit and a visual display unit, and the model establishment module comprises a model training unit, a model verification unit and a model updating unit. The data processing module comprises a radiometric calibration unit, a correction unit and a feature extraction unit, the remote sensing data acquisition module comprises a satellite remote sensing data receiving unit and an unmanned aerial vehicle remote sensing data acquisition unit, a large amount of data can be acquired in a short time through a satellite and an unmanned aerial vehicle, and the remote sensing technology can cover a wide water area; and finally, a model is established to invert a remote sensing image to obtain a suspended sediment concentration distribution diagram so as to judge a monitoring result.

The invention discloses a near-shore wave-flow field-sediment coupling simulation method considering a wave breaking nonlinear effect, and belongs to the field of near-shore hydrodynamics, and the method comprises the steps: inputting WRF high-resolution wind field, tide boundary conditions and water depth information, and initializing a wave module, a flow field module and a sediment module; calculating local wave breaking dissipated energy by adopting an improved wave breaking energy dissipation formula to obtain a wave energy density spectrum and a breaking probability; a near-shore flow field is calculated under radiation stress nonlinear correction, and hydrodynamic boundary conditions are updated; calculating sediment suspension and deposition by using a coupling diffusion coefficient, and updating sediment concentration distribution; waves, flow fields and sediment are mutually coupled through loop iteration, and coastal wave-flow field-sediment simulation is achieved under extreme conditions such as typhoons, storm surge and strong storm waves. The method can improve the prediction precision of the wave height, the flow velocity and the sediment concentration under the condition of offshore strong storm waves, and is used for typhoon storm surge prediction, harbor basin deposition evaluation and offshore ecological environment management.

The invention discloses a device for acoustically monitoring suspended sediment concentration and section particle size mean value of an ocean and a river, and relates to the technical field of ocean and river water environment monitoring. The four groups of piezoelectric ceramic transducers at the transmitting end are used for transmitting sound pulses with multiple frequencies into the same water body, and the broadband hydrophone array at the receiving end is used for synchronously receiving acoustic backward scattering signals which are scattered back. Wavelet threshold denoising and frequency domain filtering are combined, acoustic back scattering signals are preprocessed, turbulence and biological noise are eliminated, nonlinear errors caused by the particle size-concentration coupling effect are solved through an inversion algorithm fusing attenuation and scattering signals and in combination with a dynamic hierarchical data processing technology, and the accuracy of the acoustic back scattering signals is improved. The device realizes high-precision real-time measurement of suspended sediment parameters in ocean and river environments, has the capability of adaptive correction of environmental parameters, and is suitable for scientific research and engineering monitoring scenes.

The invention discloses a reservoir desilting method and device using fixed jet flow, and relates to the technical field of water conservancy and hydropower engineering desilting. According to the method, the flow speed, pressure, mud layer thickness and gradient parameters of water around a nozzle are collected in real time; calculating a jet flow angle compensation coefficient, and identifying a nozzle direction stable state; on the basis of a nozzle set with stable direction, a nozzle group is constructed and a time sequence differential control table is established by combining a topological relation between nodes and disturbance propagation characteristics, so that ordered migration of turbulent flow disturbance is realized; sediment concentration, flow velocity and flow data are collected in a flow guide plate and a sediment discharge port area, and a desilting efficiency index is calculated and used for evaluating sediment transportation continuity and flow guide performance; and a comprehensive operation optimization coefficient is generated through a multivariable adaptive weighted fusion algorithm, and the system automatically executes adaptive regulation or sends out a manual intervention prompt. According to the method, self-monitoring, self-correction and global optimization of the fixed jet system can be achieved, and the reservoir dredging efficiency and the operation stability are remarkably improved.

The invention relates to the technical field of hydraulics, in particular to a method and device for predicting the median particle size of a flocculating constituent under the action of algae, and the method comprises the steps: obtaining the sediment concentration, sediment density and water turbulent shear strength in a water body of a target area; acquiring the chlorophyll concentration of algae in the water body and acquiring the percentage of organic matters covering the surface of the sediment according to the chlorophyll concentration of algae; and obtaining model correction parameters of the target area, correcting the target prediction model by using the model correction parameters, predicting change information of the median particle size of the flocculating constituent in the water body of the target area along with time based on the corrected target prediction model, the sediment concentration, the sediment density and the turbulent shear strength of the water body, and obtaining a prediction result of the median particle size of the flocculating constituent. According to the method, the median particle sizes of the algae-mud flocculating constituent and the pure mineral flocculating constituent in the water body can be accurately predicted under the condition that only conventional parameters in the water body are determined, the calculation cost is reduced while the accuracy of a prediction result is effectively improved, and the applicability of the method is improved.

The utility model provides a water suspended sediment concentration and flow velocity monitoring device, which comprises a control box, a data acquisition box, an industrial personal computer and a cloud platform, and is characterized in that the control box comprises a data storage and transmission assembly and a power supply assembly, and the data storage and transmission assembly is used for storing data and communicating with the industrial personal computer and / or the cloud platform; the data acquisition box is used for acquiring spectral data to the sky and the ground, acquiring water body images, acquiring position information of the current device and sending the information to the data storage and transmission assembly; the industrial personal computer is used for receiving the data sent by the data storage and transmission assembly and calculating the concentration and flow velocity of suspended sediment in the water body; and the cloud platform is used for receiving and storing the data sent by the data storage and transmission component. By means of the monitoring device, in-situ monitoring is conducted on the water body, no reagent needs to be consumed, the influence of equipment on the water body environment can be reduced, the monitoring accuracy is improved, and meanwhile maintenance and installation are convenient.

The invention discloses an estuary sediment transport simulation method considering environmental factor coupling, and belongs to the technical field of offshore marine deposition dynamics, and the method comprises the steps: processing the geographic data of a target sea area, constructing a non-structural computational grid region of the target sea area, and generating an initial terrain field; for a target sea area, setting boundary conditions and an initial field, and constructing a three-dimensional hydrodynamic numerical model; performing systematic verification and parameter calibration on the three-dimensional hydrodynamic numerical model in S2 by adopting multi-source observation data; based on the three-dimensional hydrodynamic force numerical model verified in S3, constructing a three-dimensional hydrodynamic force-sediment coupling numerical model considering environmental factor driving; and performing systematic verification and parameter calibration on the three-dimensional hydrodynamic force-sediment coupling numerical model in the step S4 by adopting multi-source observation data. According to the method, the real-time dynamic coupling relation between the environmental factors and the sediment settling velocity is established by modifying the sediment settling velocity equation, the flocculation effect of the estuary high-concentration fine-particle sediment is represented, and the accuracy of suspended sediment concentration simulation is improved.

The invention discloses an online monitoring test platform for sediment characteristics of a water turbine passing through a machine, belongs to the technical field of monitoring of sediment of a hydroelectric generating set passing through the machine, provides circulating water flows with different flow velocities and sediment contents, and can be used for testing different types of sediment characteristic online monitoring systems or sensors. The applicability and the accuracy of the system or the sensor under different flow velocity conditions and different sediment concentrations can be checked, and the method can be used for development and calibration of a sediment characteristic on-line monitoring system.

The invention provides a mangrove forest growth monitoring method and system, and the method comprises the steps: obtaining a mangrove forest multi-temporal remote sensing image of a target monitoring region, extracting a spectral feature index sum of the mangrove forest multi-temporal remote sensing image, and obtaining a leaf area index based on a leaf area index model; obtaining a water body suspended sediment concentration inversion result based on a sediment content inversion model; performing spatial statistical analysis on the leaf area index and the inversion result of the suspended sediment concentration in the water body to obtain a spatial statistical index; according to the leaf area index and the water body suspended sediment concentration inversion result, the stress degree of water body suspended sediment on mangrove forest growth is analyzed, and mangrove forest growth condition change parameters are obtained; and according to the spatial statistical index and the mangrove forest growth condition change parameter, performing stress degree grading on the target monitoring area, and generating a corresponding early warning instruction. The problem that the influence of suspended sediment in the water body on mangrove forest growth cannot be recognized in time can be solved, and the mangrove forest growth monitoring accuracy is improved.

The invention provides a sediment concentration prediction method and system based on a freeze-thaw coupling physical constraint model, and relates to the technical field of sediment concentration prediction, and the method comprises the steps: obtaining hydrological data, meteorological data and various original data of soil and vegetation, and carrying out the preprocessing; constructing a benchmark sediment concentration physical model based on the multiple kinds of preprocessed original data, and constructing an input feature vector; inputting the input feature vector into a sediment concentration prediction ANN model, and outputting to obtain the sediment concentration; wherein in the training process of the sediment concentration prediction ANN model, reference sediment prediction and sediment mass conservation constraint of the physical model are introduced into an ANN model loss function, the loss function is enhanced by adopting a freeze-thaw weighting strategy, and the sediment concentration prediction ANN model in which the physical model and the ANN model are deeply fused is obtained. According to the invention, the stability and accuracy of prediction during extreme rainfall, runoff surge or frequent freezing and thawing are improved.

The present invention discloses a method, system and device for estimating the suspended sediment concentration of a river, which relates to the field of retrieving the suspended sediment concentration of a river in an ultra-large value range, and includes: obtaining a measured data set of historical river suspended sediment concentration; obtaining the water body reflectance of images of multiple satellites; generating a matching sample pair data set and dividing it into training samples and validation samples; constructing a band combination mainly based on the required bands as the bands reflecting the characteristics of the suspended sediment concentration in high-concentration water bodies, and obtaining the sensitivity index RAN; constructing an inversion model using the training samples and the sensitivity index RAN; obtaining the river range; using a cloud computing platform to analyze the image sets of multiple satellites using the river range, the sensitivity index RAN and the inversion model to obtain the spatial distribution information of the river suspended sediment concentration; obtaining the spatial distribution information of the river suspended sediment concentration. The present invention can accurately evaluate the suspended sediment concentration of a river.

The invention discloses a cross section water depth continuous measurement method and system based on millimeter waves, and relates to the technical field of hydrographic measurement. According to the invention, through a millimeter wave radar array and a multiple-input-multiple-output antenna, a frequency modulation continuous wave signal is transmitted and a mixed echo signal is received; extracting time-frequency characteristics by using wavelet transform and short-time Fourier transform, and classifying reflection peaks in combination with a Gaussian mixture model; calculating the thickness of an ice layer, the thickness of an air interlayer and an initial water level based on the delay inequality, and dynamically correcting an error through adaptive Kalman filtering; a dynamic focusing algorithm is adopted to synthesize water surface and riverbed reflection signals, and a sand content compensation and flow velocity correction model is introduced to optimize water depth and riverbed elevation inversion; the three-dimensional interpolation weight is optimized through an ant population algorithm, and a high-precision cross section continuous water depth distribution diagram is generated; according to the invention, the problems of poor penetrability, weak anti-interference capability and low continuous water depth precision are solved, and full-section dynamic monitoring of the ice layer thickness, the water level, the water depth and the riverbed form is realized.

A water body suspended sediment concentration monitoring method based on FUI water body classification comprises the steps that firstly, a target watershed Sentinel-2 L1C image from a certain year to a certain year is obtained from GEE, and after resampling is conducted till the resolution is 10 m, preprocessing such as 6S model atmospheric correction, proximity effect correction and quality control is conducted; 5 wave bands are used for calculating spectral angles to obtain FUI, and 14 is used as a threshold value to divide the water body into clear water and muddy water. And then selecting an optimal wave band combination according to the FUI classification to construct a semi-empirical inversion model, and finally calculating the suspended sediment concentration distribution by using the model and verifying the suspended sediment concentration distribution. The method solves the problem that the model generalization ability is low in the monitoring of the suspended sediment concentration of the target drainage basin, and the inversion precision is high.

The invention discloses an FPGA-based sound wave multiple reflection sediment concentration measurement method. The method comprises the following steps: constructing an ultrasonic underwater measurement system capable of realizing ultrasonic multiple reflection and driving the ultrasonic underwater measurement system to work; an ultrasonic transducer is driven by the FPGA to emit ultrasonic waves; echo signals of the ultrasonic waves passing through the turbid liquid are collected, subjected to analog-to-digital conversion and then transmitted to the FPGA; digital filtering and peak detection are carried out on the echo data based on the FPGA; according to a peak value detection result, an ultrasonic attenuation coefficient is calculated based on the FPGA in combination with numerical integration; for a plurality of turbid liquid bodies of the same type with known sediment concentrations, the second step to the fifth step are executed respectively, ultrasonic attenuation coefficients under different concentrations are obtained, and then fitting is conducted on the ultrasonic attenuation coefficients and the concentrations to obtain a regression equation of the attenuation coefficients and the sediment concentrations; and executing the second step to the sixth step to obtain an ultrasonic attenuation coefficient aiming at a to-be-detected turbid liquid body, and substituting the ultrasonic attenuation coefficient into the regression equation to obtain the sediment concentration of the to-be-detected turbid liquid body. According to the method, the defects of the traditional method in real-time performance and precision are overcome, and the real-time performance and accuracy of sediment concentration measurement are remarkably improved.

The invention provides a suspended sediment concentration inversion method capable of resisting particle size interference, which comprises the following steps of: standardizing the original acoustic echo intensity of each observation grid to obtain the standardized volume back scattering intensity; establishing a sonar equation considering the sound wave attenuation of the sediment particles, and performing explicit processing on the sonar equation considering the sound wave attenuation of the sediment particles to obtain an explicit inversion model which resists particle size interference and considers the on-way change of the sediment particle size; and performing model parameter calibration on the explicit inversion model, and performing suspended sediment concentration inversion on the river observation section based on the suspended sediment concentration inversion value of each observation grid. According to the method, the dependence of ADCP inversion of the suspended sediment concentration on suspended sediment particle size distribution is effectively eliminated, and the stability and accuracy of suspended sediment concentration inversion are improved. The particle size interference resistant explicit method can realize continuous and real-time suspended sediment concentration monitoring, and is suitable for various water environments such as rivers, lakes, reservoirs and the like.

The invention relates to the technical field of sediment and bubble monitoring, in particular to a sediment and bubble concentration monitoring device and method.The sediment and bubble concentration monitoring device comprises a laser transmitter, a light sensor, a light coupler, a light transmitting piece, an image obtaining device and a beam splitter, and further comprises an electromagnetic flowmeter and a detector which are arranged on a pipeline module; the laser transmitter, the spectroscope and the image acquisition device are placed at fixed positions in the shell so as to shoot silt and gas particles in the flowing pipeline, and then data are transmitted to the processor; a processor calculates the concentration of sediment and bubbles in a pipeline through data preprocessing of a k-Mean clustering algorithm, median filtering and connected domain analysis and a CNN convolutional neural network algorithm, and in the prior art, only the sediment concentration can be measured, but the concentration of gas cannot be monitored at the same time. According to the invention, the content of silt and gas and the influence on hydraulic machinery can be monitored at the same time, timely early warning is provided, and the operation efficiency and safety of equipment are effectively improved.

The invention discloses a method and device for determining the depth of a silt preparation pit of a canal project and electronic equipment, and relates to the field of river channel desilting engineering.The method comprises the steps that the topographic features and the river trend of a target canal project in each project river reach are obtained, inputting the topographic features and the river trend of each project river reach into a pre-established water-sediment coupling dynamic model, solving water-sediment element information in each time step length by the water-sediment coupling dynamic model, and outputting sediment deposition data of different project river reaches; obtaining river channel parameters of each project river reach, and calculating a river section sand content change condition based on the river channel parameters; and on the basis of the river section sand content change condition and the river section water flow of the project river reach, calculating the on-way section accumulated deposition thickness, and determining the depth of each silt preparation pit on the basis of the on-way section accumulated deposition thickness. The technical problems that in the prior art, a dredger needs to dredge from a channel starting point to a channel ending point, the oil consumption of the dredger is large, and the efficiency is low are solved.

The invention relates to the technical field of suspended sediment dynamic monitoring, in particular to a suspended sediment dynamic change monitoring and deep sea operation scheduling optimization method, which comprises the steps of multi-source fusion data acquisition: synchronously acquiring suspended sediment concentration distribution data, three-dimensional ocean current vector data and seabed microtopography slope data of a target area; simulation of plume dynamic diffusion: inputting the acquired data into a microtopography coupled adaptive plume diffusion model to generate a plume diffusion three-dimensional space-time cloud picture in the future 6 hours; dynamic risk partition generation: performing space-time overlay analysis on the plume diffusion three-dimensional space-time cloud picture and a preset ecological sensitive area dynamic electronic fence to obtain an operation risk thermodynamic diagram; and intelligent partition scheduling execution: dynamically dividing a mining prohibited area, a buffer area and a safe area, and sending an inter-partition rotation scheduling instruction to the mining equipment group. According to the method, the spatial resolution and the aging response capability of sediment diffusion behavior prediction are improved, and a basis is provided for environmental impact assessment and ecological protection.

The embodiment of the invention provides a water and sediment concentration and water quality multi-index automatic monitoring and analyzing device for a southern Xinjiang canal system, and relates to the technical field of environment monitoring. Comprising a steel rope connecting ring, the outer wall of the steel rope connecting ring is rotatably connected with a collecting frame, and the bottom of the collecting frame is fixedly connected with a counterweight circular plate. The rotating rod drives a driving bevel gear to rotate, the driving bevel gear drives a driven bevel gear and the rotating rod to rotate, the rotating rod drives a propeller to rotate, the propeller sucks water into a pressure suction cylinder through a filtering water inlet pipe so that the gravity of the device can be increased, redundant water is discharged out of a water discharging pipe, and through propelling force generated by discharged water flow, the water is discharged out of the water discharging pipe. The equipment can accelerate the settling velocity and quickly reach a predetermined detection water area, so that the sampling time is greatly shortened, and the working efficiency is also remarkably improved.

The invention discloses a sediment prediction method and system for oscillation period strategy snow ablation optimization, and the method comprises the steps: obtaining sediment data characteristics, enabling a drainage basin to comprise a plurality of nodes, and calculating the snow melting runoff of each node according to the sediment data characteristics; according to the snow melting runoff of each node, calculating the initial sand production concentration of each node; and constructing a sediment prediction model, inputting sediment characteristic data and corresponding actual sediment concentration to the sediment prediction model to obtain a trained sediment prediction model, inputting real-time sediment data to the trained sediment prediction model, and outputting predicted sediment concentration by the trained sediment prediction model. According to the method, historical sediment data are acquired, and a graph convolutional neural network is constructed for learning complex nonlinear mapping from snow melting-runoff generation to sediment transportation, so that the problems of weak generalization ability and strong data dependence of an existing snow melting period sediment prediction method are solved.

The invention discloses an in-situ suspended sediment concentration and flux prediction system based on conductivity data, and relates to the technical field of marine environment in-situ monitoring, the in-situ suspended sediment concentration and flux prediction system comprises a data processing and visualization platform, the data processing and visualization platform is in communication connection with the following modules: a data acquisition module, a data processing module, a data processing module and a data processing module, the method is used for extracting multi-dimensional water body data collected in an in-situ environment from a database. According to the method, a continuous vertical concentration-flow velocity matrix is generated through coupling corrected suspended sediment concentration data and flow velocity data, a flux prediction model is established in combination with historical data, a nonlinear relationship between sediment transportation flux and flow velocity-concentration is analyzed, and a random forest algorithm is adopted to determine the flow velocity-concentration of the sediment. The flow velocity, the conductivity interval depth and the corrected suspended sediment concentration serve as input variables, a sediment flux prediction value is output, static and dynamic comprehensive prediction of sediment fluxes at different moments and at different positions is achieved, and a quantitative analysis tool is provided for ocean sediment dynamic research and mineral environment evaluation.

The invention discloses an anti-wear mixed-flow water turbine set for high water head, high rotating speed and high sand content, and belongs to the technical field of mixed-flow water turbines. Comprising a volute and a main shaft, one end of the main shaft penetrates through the volute and is fixedly connected with a rotating wheel located in the volute, and blades are evenly distributed on the inner side of the rotating wheel; water is guided into the water inlet pipe in the tangential direction through the guide-in pipe, then spiral water flow descending can be formed, sediment and water can be better separated under the action of centrifugal force through cooperation of the sediment removal structure, the filtered and intercepted sediment can be discharged out of the filter cartridge in time, the situation that follow-up water flowing is affected due to blockage is avoided, and the service life of the filter cartridge is prolonged. Meanwhile, abrasion caused by impact of small silt to the blades can be effectively blocked through the protection blocks, and meanwhile the collection channel is arranged and can be used for intercepting and collecting the silt.

The invention relates to the technical field of sediment prediction, in particular to a method for predicting sediment deposition in a channel based on a hydrodynamic model. Comprising the following steps: correcting the critical start-up flow velocity of the sediment according to the biomass, metabolic rate and biological membrane thickness of a microbial community to obtain a corrected critical start-up flow velocity; on the basis of the corrected critical starting flow velocity, the actual suspended sediment concentration in the navigation channel is calculated in combination with the turbulence intensity, the propagation distance and the ship draught depth of ship wake flow; according to the suspended sediment concentration, the sediment deposition amount in the channel is calculated by combining the cementation strength, the water content and the organic matter decomposition rate of the sediment on the surface layer of the riverbed. According to the method, ecological and navigation related influence factors can be comprehensively considered, and the prediction accuracy in a complex scene is improved.

The application relates to the technical field of marine hydrological monitoring, and discloses a seawater suspended sediment concentration low-altitude observation method, which uses a low-altitude observation platform to carry digital photography equipment, obtains seawater suspended sediment concentration images, collects water samples in the photographed sea area, positions the water samples through a global satellite positioning system, uses a filtering method to measure the suspended sediment content, pre-processes the obtained seawater suspended sediment concentration images, realizes automatic splicing of the images and automatic imaging of orthographic images, trains the processed image data and the measured suspended sediment concentration data based on an optimized artificial neural network algorithm, establishes a seawater suspended sediment concentration inversion model, and evaluates the model precision. The method uses the low-altitude observation platform to obtain high-resolution images, uses the optimized artificial neural network model to invert the suspended sediment concentration, has the advantages of high precision, low cost, flexibility, timeliness and the like, and can effectively make up for the deficiency of satellite remote sensing.