11 results about "Current velocity" patented technology

The invention belongs to the technical field of ocean surface flow velocity remote sensing measurement, and particularly relates to a Luoga No.2 SAR (Synthetic Aperture Radar) flow velocity correction method based on Bragg orbit velocity, which comprises the following steps of: verifying the physical correctness of an orbit velocity mechanism relative to a phase velocity mechanism; under a DopRIM framework, a physically consistent sea wave error correction model is established; calibrating parameters of the sea wave error correction model; applying the calibrated sea wave error correction model to along-orbit interference SAR observation data of the Luoma No. 2 satellite, and calculating the radial surface flow velocity and sea wave error of each resolution unit; comparing an output result with a matched reference truth value to evaluate the effectiveness of the sea wave error correction model; comparing the sea wave error correction model with a KaDOP model, and respectively counting and analyzing simulated sea wave errors under different methods; the sea wave error simulation result is visually displayed, and the improvement effect is quantitatively evaluated through in-situ observation data and a KaDOP simulation result.

This invention discloses a multi-scale time-frequency analysis method and system for ocean current meter signal processing, relating to the field of marine information processing. The method includes: S1: acquiring raw data and performing physical benchmark correction to obtain three-dimensional current velocity data and basic mass labels; S2: extracting first and second features from the three-dimensional current velocity data through spatiotemporal decoupling; S3: fusing and separating the three-dimensional current velocity data based on the first and second features to obtain an optimized set of flow field parameters, and generating the uncertainty of each parameter by combining the basic mass labels and error source information; S4: performing comprehensive quality assessment and grading based on the first and second features and the uncertainty, outputting a data product with mass labels and uncertainty information. By extracting spatiotemporal dual-dimensional features and using them to guide signal fusion and quality assessment, highly robust processing of ocean current data and end-to-end quality traceability are achieved, significantly improving the reliability of the data product.

The invention discloses a gate base leakage diagnosis device and method fused with elastic wave sensing, and relates to the technical field of gate base leakage diagnosis. Elastic wave characteristics, fluid pressure data, water flow velocity data and temperature data of the target area in the current period are collected according to a calibration sampling strategy; and carrying out feature level fusion on the elastic wave features, the fluid pressure data, the water flow velocity data and the temperature data of the current period to obtain an enhanced fusion feature vector. According to the method, dynamic self-adaption of the sampling frequency is achieved by forming a dynamic self-adaption monitoring closed loop, and compared with a global coverage mode of inherent sampling frequency of a traditional monitoring mode, sufficient sampling data of a high-risk area is guaranteed by adjusting a targeted sampling strategy, so that the sampling efficiency of the high-risk area is improved. Therefore, the accuracy of the diagnosis result and the diagnosis efficiency are effectively improved.

The present application belongs to the technical field of remote sensing measurement of ocean surface current velocity, and in particular to a Lujia-2 SAR current velocity correction method based on Bragg orbital velocity, comprising the following steps: verifying the physical correctness of the orbital velocity mechanism relative to the phase velocity mechanism; and under the DopRIM framework, establishing a physically consistent sea wave error correction model; calibrating the parameters of the sea wave error correction model; applying the calibrated sea wave error correction model to Lujia-2 satellite along-track interferometric SAR observation data to calculate the radial surface current velocity and sea wave error of each resolution unit; comparing the output results with the matched reference true value to evaluate the effectiveness of the sea wave error correction model; comparing the sea wave error correction model with the KaDOP model, respectively, to statistically analyze the simulated sea wave error under different methods; visualizing the sea wave error simulation results, and quantitatively evaluating the improvement effect through in-situ observation data and KaDOP simulation results.

The present application relates to the technical field of water flow profile correction, in particular to a multi-beam cooperative water flow profile dynamic correction system based on ADCP, which comprises a multi-beam ADCP cooperative sensing array, an environmental parameter sensing module, a dynamic correction and fusion module, a data feedback and communication network and a visualization terminal. The multi-beam cooperative water flow profile dynamic correction system and method based on ADCP breaks through the single-beam measurement blind area by constructing a multi-beam ADCP cooperative measurement network and synchronously collecting water flow velocity data at different azimuths and depths. At the same time, a dynamic correction algorithm is designed to combine real-time water flow turbulence intensity, water sound velocity profile and other environmental parameters to perform real-time fusion and deviation correction on multi-beam data. A data feedback closed loop is built to real-time return the corrected water flow profile data to the measurement terminal, realize dynamic iteration of measurement-correction-output, and improve the accuracy and timeliness of water flow profile measurement in complex water areas (such as estuary and reservoir area).

The invention discloses a UUV (Unmanned Underwater Vehicle) route self-adaptive adjustment method based on ocean current and pose information fusion, which comprises the following steps: step 1, carrying an acoustic Doppler ocean current profiler on a UUV, measuring the ocean current flow velocity under a beam coordinate system, and carrying out integration processing by combining the position and pose data of the UUV to obtain ocean information combined with the pose of the UUV; step 2, calculating the optimal initial course of UUV navigation according to the ocean information combined with the UUV pose obtained in the step 1; step 3, judging whether the result calculated in the step 2 is interfered by navigation interference factors, if so, executing step 4, and if not, outputting the optimal initial course; and 4, calculating the course of the UUV when the UUV is interfered by the navigation interference factors, calculating the optimal course after the UUV is interfered according to the information obtained in the step 2, and outputting the optimal course after the UUV is interfered. According to the method, the UUV can be adjusted to the optimal route through adaptive adjustment of the route, so that the navigation efficiency is improved while the task is ensured to be completed.

The invention provides an improved method, device, equipment and medium for inverting interval velocity by using a first arrival wave, and the method comprises the steps: obtaining an actually measured wave field value, calculating the derivative of the actually measured wave field value, and picking up the first arrival time of a seismic record corresponding to the actually measured wave field value; determining an initial speed model; solving a wave field value calculated by using the current speed model, and calculating a derivative of the wave field value; calculating first arrival time from the excitation point and the receiving point to each grid point in the speed model; determining a propagation path of a first arrival wave; calculating to obtain a new speed model; whether the new speed model meets the precision is judged, and if the new speed model meets the precision, the current speed model is an inversion speed model; and if the precision is not met, repeating iteration to construct a new speed module until the new speed model meets the precision. According to the technical scheme, the precision of the inversion speed model can be improved to a large extent, the speed resolution is greatly improved, the anti-interference performance is high, and the interference of noise on seismic signals can be well suppressed.

This invention discloses a method for controlling the leakage velocity of phase change materials (PCMs) under high flow rates, comprising: acquiring initial configuration data of the target leakage channel and characteristic model parameters of the PCM; real-time acquisition of fluid state observation sequences of the leakage channel; inverting the real-time equivalent geometric parameters and flow field characteristic parameters of the channel based on the observation sequences; estimating the residence time window of the injected grout in the channel; estimating the phase change solidification time window by combining the characteristic model parameters and the observation sequences; determining the control criterion index based on the ratio of the residence time window to the phase change solidification time window; generating an adaptive control vector based on the control criterion index, driving the actuator to adjust the injection parameters until the flow rate control termination condition is met. This invention utilizes the solidification and residence of the PCM in the leakage channel to form a hindrance, reducing the water flow velocity in the high-velocity leakage channel to the workable range of traditional grouting methods, creating low-velocity conditions for subsequent seepage prevention treatment.

This invention relates to the field of marine geological monitoring technology, specifically to a machine learning-based method for time-series prediction of seabed movement, comprising the following steps: S1, collecting multi-source time-series data such as seabed elevation, waves, tidal currents, wind field, sediment concentration, bottom current velocity, and geostress; S2, performing time alignment, missing value imputation, and normalization preprocessing; S3, extracting time-series features using ConvLSTM to generate a multi-dimensional time-series feature sequence; S4, calculating the time-series correlation strength and performing dimensionality reduction based on EOF to obtain a correlation feature sequence; S5, introducing meteorological parameters to construct an enhanced input vector, forming a seabed movement prediction rule set; S6, training the mapping relationship based on the rule set using a three-stage mechanism, and jointly evaluating the prediction accuracy using RMSE and Pearson coefficient. This invention achieves high-precision and stable prediction of seabed movement trends by constructing a prediction rule set that integrates dimensionality-reduced features and meteorological factors, and by employing a three-stage mechanism to train and evaluate the mapping relationship.

The application provides a 10-meter buoy current correction method based on an external GNSS, a medium and a system, and belongs to the technical field of current correction.The application is characterized in that a heading angle is used to replace a built-in magnetic compass heading in real time;then a heading correction amount and a current velocity vector correction amount of each depth layer are jointly optimized by an artificial intelligence multi-task joint estimation correction model, loss weights are dynamically adjusted in combination with a channel credibility evaluation function, and a weak sensor link in terms of credibility is isolated through a fault isolation algorithm based on the maximum flow and minimum cut theorem of a flow graph;finally, sea current profile data with a data quality grade identifier are output through direction consistency verification and a flow velocity direction consistency index adaptive adjustment. Thus, the technical problem that, when a buoy integrates an acoustic Doppler current profiler, magnetic interference causes heading angle distortion and further causes a serious deviation of a sea current profile flow direction, and existing means cannot continuously and reliably correct the heading angle in complex sea conditions is solved.

The invention discloses a non-contact riverway surface flow velocity measurement method, which comprises the following steps of: 1, acquiring a current video image of a riverway to be measured, determining a current effective velocity measurement area and an actual width thereof, and identifying a current real floating object target; 2, tracking the current real floating object target, judging whether the current real floating object target enters the current effective speed measurement area or not in the tracking process, and executing the step 3 when the judgment result is that the current real floating object target enters the current effective speed measurement area; and step 3, calculating the speed of the current real floating object target so as to obtain the current flow velocity of the to-be-measured river channel. The method greatly improves the estimation accuracy of the water flow velocity on the surface of the river channel, and has a very high application value.