1613 results about "Tomography" patented technology

The invention relates to the technical field of power transformer state monitoring, and discloses a main transformer winding temperature rise on-line monitoring method and system, and the method comprises the steps: obtaining the calibration flight time of ultrasonic waves through an acoustic sensor array disposed on the outer wall of an oil tank in a quasi-isothermal state of a transformer; calculating a structure additional time delay which is caused by an internal fixed structure and does not change along with the temperature, and establishing an acoustic fingerprint for the transformer; during on-line monitoring, oil way net propagation time reflecting temperature change of the insulating oil is obtained from on-line flight time measured in real time; and then, based on the net propagation time of the oil way, an acoustic tomography algorithm is adopted to reconstruct internal two-dimensional or three-dimensional temperature field distribution, and the winding hot-spot temperature is finally and accurately calculated in combination with the real-time load current. According to the invention, through the acoustic fingerprint correction technology, the measurement interference of an internal fixed structure is eliminated, and non-intrusive, high-precision and visual online monitoring of the winding hot-spot temperature is realized.

The present technology pertains to systems and methods for one-way authentication of quantum channels. A transmitter generates an entangled quantum state comprising a first state and a second state, modulates the second state according to a clock-synchronized pattern, and transmits it through a quantum channel to a receiver. The first state is retained and measured at the transmitter to extract quantum-state information. Authentication is performed based on this information, without requiring feedback from the receiver. The quantum-state information may be derived using quadrature measurements, Gaussian tomography, or other statistical analyses to detect whether the second state underwent irreversible interactions such as eavesdropping or decoherence. The system enables secure unidirectional quantum authentication, reduces protocol complexity, and supports real-time anomaly detection. It is compatible with continuous-variable quantum states, quantum key distribution (QKD), and scalable communication architectures.

The invention discloses a water vapor chromatography modeling method and device based on GNSS-MET, and belongs to the technical field of atmospheric water vapor information inversion. According to the method, satellite signals and meteorological parameters are obtained through a GNSS-MET receiver, and the oblique path water vapor content (SWV) is calculated to serve as chromatography input; densely and uniformly distributed observation stations are selected to construct a chromatography area, and voxel grids are divided; a horizontal constraint is constructed by using Gaussian distance weighting, a vertical constraint is constructed in combination with a water vapor vertical index distribution characteristic, and ERA5 reanalysis data is introduced as a prior constraint, so that the limitation of a traditional sounding data constraint is solved; and resolving the tomographic equation through a singular value decomposition (SVD) method to obtain three-dimensional water vapor density distribution. According to the method, the high temporal-spatial resolution characteristic of ERA5 data is utilized, the precision and reliability of water vapor chromatography are remarkably improved, and the method is suitable for the fields of extreme weather prediction, meteorological monitoring and the like.

The invention relates to the technical field of industrial vision, in particular to a ceramic glazed tile internal defect detection method based on image recognition, which comprises the following steps: acquiring multi-modal data including an X-ray tomography sequence, a surface heat map, a visible light image and production process parameters; constructing a three-dimensional digital twin based on X-ray data, fusing surface image information, and utilizing a three-dimensional segmentation network to accurately identify three-dimensional geometric features of internal and underglaze defects; carrying out physical causal reasoning on the geometrical characteristics of the defects through the constructed defect-cause knowledge graph reasoning model, and intelligently matching and identifying the physical causes of the defects; targeted correlation analysis and traceability are performed in combination with physical causes and production process parameters, production links causing defects are accurately positioned, and a control instruction for optimizing production is generated. According to the method, closed-loop defect detection of'diagnosis-traceability-control 'is realized, the defect problem can be accurately positioned, and automatic decision support is provided for optimizing production and improving product quality.

The invention discloses a reservoir dam body deformation monitoring system, and relates to the technical field of hydraulic engineering safety monitoring. The problems that the data acquisition dimension is single, the real state of a dam body under the complex working condition is difficult to comprehensively present, the depth detection capability on the internal structure of the dam body is lacked, and the deformation trend of the dam body is difficult to accurately predict are solved. Through comprehensive consideration of interaction of a displacement field, a stress field, a temperature field and a hydraulic field, the dam body mechanical state and the deformation trend are accurately evaluated, the internal defects of the dam body are rapidly and accurately detected by means of an elastic wave tomography technology, a key basis is provided for dam body maintenance and reinforcement, the defect identification capability of the system is improved, and the system has a wide application prospect. A dynamic risk assessment technology is adopted, historical and real-time data are combined to update the dam body deformation state transition probability, potential safety hazards are found in advance, a complete closed-loop monitoring system is constructed, all-weather intelligent guarantee is achieved, monitoring accuracy, timeliness and reliability are remarkably improved, and safe operation of a reservoir is effectively guaranteed.

The invention discloses an electroplating quality monitoring method, device and equipment for an MLCC capacitor and a medium, and relates to the technical field of MLCC capacitor electroplating. The electroplating quality monitoring method comprises the following steps: firstly, acquiring coating microstructure and ion migration data by adopting X-ray tomography and electrochemical impedance spectroscopy technologies, and performing defect classification in combination with appearance detection data; electroplating process parameters are obtained, and a multi-dimensional feature library is constructed through principal component analysis. Then based on a defect classification result and a feature library, training an improved random forest model to realize multi-defect prediction, screening key process parameters through sensitivity ranking, and establishing defect-parameter association; and then constructing an attribution model to analyze an influence mechanism of process parameters on defects. In actual production, real-time process parameters are input into the prediction model for online quality monitoring; and when defects appear, reversely tracing cause parameters through an attribution model. According to the method, a system of data acquisition, feature fusion, real-time monitoring and defect tracing is formed, and the electroplating quality can be effectively monitored.

The invention discloses a power distribution network automation control method and system with a fault self-recognition function, particularly relates to the technical field of power distribution network automation, and aims to solve the problem that the power distribution network is not damaged under the conditions of sparse measuring points, communication jitter, grid-connected moisture regain and inconsistent topology and timestamp of the power distribution network. And the problems of misjudgment, missed judgment and difficult identification result landing caused by load disturbance submerging of fault features and incapability of self-certification of a topological state are solved. A double-anchor time base is constructed, an idempotent bond is generated through out-of-order buffering, water line advancing and playback to complete alignment, and main candidates are determined in cooperation with a trigger type snapshot matrix, incremental impedance tomography and direction consistency; the method comprises the following steps: extracting hysteretic area, amplitude-phase transition and slope curvature characteristics under same-layer gating, combining an arrival time sequence and attenuation law positioning, generating an execution list containing sequence, interlocking, secondary confirmation and withdrawing through residue checking, and solidifying an evidence chain, so that reliable self-recognition and execution can still be realized under the conditions of sparse measuring points, communication jitter and moisture regain.

The invention provides a DICOM (Digital Imaging and Communications in Medicine) file sequence processing method, a medical image analysis method, system and device, a computer storage medium and a computer program product, the processing method comprises the following steps: loading a DICOM file sequence corresponding to a series of image sets obtained by tomography, and arranging according to a scanning sequence to obtain an initial image file queue; reading DICOM files from a specified position to form a key image file queue with a fixed length; and reading sequence-level DICOM metadata and image-level DICOM metadata for representing key features from the key image file queue, and arranging the sequence-level DICOM metadata and the image-level DICOM metadata according to a preset rule to obtain a sequence DICOM metadata queue with fixed length and fixed information items of each position. By adopting the scheme provided by the invention, the obtained metadata queue with the fixed dimension provides a data basis for subsequent deep learning network input, and improvement of the adaptability with the deep learning network and improvement of the analysis accuracy are facilitated.

The invention belongs to the technical field of structural damage monitoring, and particularly relates to a structural dynamic tomography and damage monitoring method using self-excitation waves, which comprises the following steps: S1, carrying out spatial discretization processing on a monitored object, and establishing a three-dimensional discrete model; arranging a plurality of sensors on a monitoring object; recording the space coordinates of each sensor; s2, applying external excitation to a known position, and inverting an initial wave velocity field in the monitoring object; s3, extracting self-excitation waves of the monitored object received by each sensor; s4, identifying the arrival time of each self-excitation wave signal on each sensor; the space coordinates of the wave source of each excitation wave signal are calculated through inversion; s5, synchronously updating the wave velocity field based on the space coordinates of the wave sources of the respective excitation waves, and processing to obtain a damage result of the monitored object; and S6, performing corresponding processing based on a damage result. According to the method, dynamic tomography and real-time monitoring of the damage position, range and evolution process can be realized.

The invention discloses a multi-wave chromatography and reflection combined detection method and device for a thin-covering-layer urban active fault and a medium. The method comprises the steps that longitudinal wave seismic data and transverse wave seismic data are collected; recording vertical component data based on the longitudinal wave seismic data for first arrival travel time pickup and tomography inversion to obtain a longitudinal wave velocity structure model Vp; extracting Rayleigh surface wave frequency dispersion through the vertical component data and carrying out multichannel surface wave analysis inversion to obtain a transverse wave velocity structure model Vs; calculating a longitudinal and transverse wave velocity ratio parameter structure model Vp / Vs, and calculating to obtain a Poisson's ratio parameter structure model v; obtaining a longitudinal wave (P wave) reflection profile and a transverse wave (S wave) reflection profile; identifying and summarizing into an interpretation fracture set Fc, and recording key elements; and by taking the interpretation fracture set Fc as a structural skeleton, completing unified registration and superposition display on Vp, Vs, Vp / Vs and v, a longitudinal wave reflection profile and a transverse wave reflection profile, and outputting a shallow underground structure comprehensive interpretation map of the thin covering layer region.

The invention relates to the field of field engineering characteristic evaluation, in particular to a fracture characteristic calculation method based on resistivity tomography and resistivity static sounding. The method comprises the steps that firstly, in-situ site resistivity parameter calibration is carried out through a resistivity static sounding (RCPTU) test technology, and a resistivity index background value of a target site is obtained; then, acquiring an initial value of the electrical resistivity of the whole area of the target site by adopting a three-dimensional electrical resistivity tomography (ERT) technology; and finally, according to the resistivity-fracture inversion model, identifying the fracture distribution condition of the whole region of the target site, and giving a fracture rate evaluation model of the target site. According to the method, the precision problem of single in-situ test equipment is solved, the test precision of site three-dimensional resistivity parameters is improved, the reliability of three-dimensional inversion calculation is improved, and the three-dimensional space distribution of the soil body fractures can be evaluated quickly, nondestructively and accurately.

The invention discloses a reflective steel pipe weld defect identification method based on a multimode spectrum chromatography technology, and provides a detection process of multiband reflection data acquisition, denoising and normalization, multi-region feature distribution modeling, sparse reconstruction separation abnormal response, multi-scale contrast weighted enhancement, significant layered imaging and defect classification and discrimination. According to the method, through the measures of automatic partitioning, environment and material dynamic acquisition, self-adaptive parameter optimization and the like, high-reflection interference is effectively suppressed, the distinguishing between defects and backgrounds is remarkably enhanced, and the detection sensitivity and the positioning precision of the small and micro defects are improved.

The invention discloses a composite material stress distribution analysis method and system and a storage medium. The method comprises the following steps: acquiring a defect detection image obtained by computed tomography or infrared thermal imaging; identifying a defect area in the composite material structure and extracting defect information; according to the defect information and the loading direction, calculating a defect-induced stress enhancement factor and a stress transfer function, and constructing a stress correction factor distribution diagram; establishing a reference finite element model ignoring defects, and calculating a reference stress distribution field; acting the correction factor distribution diagram on the reference stress field to generate a correction stress distribution diagram; combining defect identification errors and material statistical fluctuation to construct an uncertainty propagation model, quantifying the corrected stress diagram, and outputting a stress value interval map; and finally, jointly correcting the stress map and the interval map, and identifying a high-risk area.

The invention provides a remote sensing image cloud removal method and system fusing gradient fidelity and time-spectrum consistency, and relates to the technical field of remote sensing image processing and tensor modeling, and the method comprises the steps: firstly obtaining a multi-temporal remote sensing image and cloud mask data, and generating a fault mask through active fault recognition; then calculating a guide gradient tensor and carrying out low-rank approximate processing to obtain a spatial characteristic factor and a time-spectrum characteristic factor; constructing a multi-objective optimization model of a gradient domain fidelity term, a pixel domain fidelity term and a time-spectrum consistency constraint term based on the multi-objective optimization model; and a near-end alternating minimization algorithm of an embedded alternating direction multiplier method is adopted to efficiently solve, a reconstruction result is corrected in combination with a cloud mask and an active fault mask, and a high-quality cloud-removed image sequence is output. According to the method, the edge structure, texture details and space-time consistency of the image can be effectively kept in a complex cloud coverage scene, and the usability and analysis value of remote sensing data are remarkably improved.

The invention discloses a microscopic crack dynamic in-situ characterization method, and relates to the technical field of crack in-situ detection. According to the method, a plurality of hardened cement paste bodies are soaked in a sulfate solution, the porosity development trend of the hardened cement paste bodies is obtained through a nuclear magnetic resonance test and a mercury injection test in the soaking process, a test sample and a test sample are prepared after soaking is finished, and the crack propagation length of the test sample is measured through a scanning electron microscope. According to the distance gradient between the sampling angle of the test sample and the exposed surface, space coordinates of crack cracking are converted into a time process along the center axis of the test sample, a delay microscope is established on the microscale, and the test sample is scanned by using X-ray computed tomography equipment in a matched mode; a crack propagation animation image is formed based on a crack form between adjacent X-ray tomography slices, and a crack development process is obtained by continuously capturing high-resolution images, so that omission of time information is avoided, and in-situ detection of microscopic cracks in a hardened cement paste sample is realized.

The disclosure provides a method and device for velocity tomography imaging of seabed shallow media, and electronic equipment. The method includes performing multichannel analyses of Guided-P and Scholte waves on seabed multi-component seismic gathers to determine measured multi-order dispersion curves of the two waves; based on a first seabed shallow media model and a theoretical dispersion equation of Guided-P wave, performing joint inversion of multi-order dispersion curves of Guided-P wave to iteratively update the P-wave velocity of seabed media; based on a second seabed shallow media model and a theoretical dispersion equation of Scholte wave, performing joint inversion of multi-order dispersion curves of Scholte wave to iteratively update the S-wave velocity of seabed media under the constraint of the P-wave velocity determined by the Guided-P wave dispersion inversion; and performing tomography imaging of seabed velocity structures with the inverted P-wave and S-wave velocities along a survey line.

A computer cuts out, from a tomographic image obtained by imaging the inside of a human body, a plurality of partial images, which include the same position in the tomographic image and have different sizes, calculates a probability of each of the plurality of partial images being a region of a specified lesion, calculates an integrated value by integrating the probabilities calculated from the plurality of partial images using a calculation that increases a contribution of probabilities calculated from partial images corresponding to at least an intermediate size out of the plurality of partial images, and identifies the same position as a region of the specified lesion when the integrated value exceeds a predetermined threshold.

The present invention relates to the technical field of dental medical treatment, and specifically discloses a method for using a CBCT (Cone Beam Computer Tomography) for automatically positioning a tooth, which comprises the following steps: S01, archiving CT data; S02, calculating AI and generating AI results; S03, entering CT reading by a client; S04, downloading and loading the CT data; S05, opening a function of a tooth lens; S06, selecting a corresponding tooth position in a tooth position list; and S07, selecting a 3D tooth rendering mode. The function of the ‘tooth lens’ is added into traditional CT reading, which is suitable for clinical disease diagnoses such as ‘tooth extraction, root canal therapy, tooth repair’ and the like in oral treatment, and doctors can precisely and quickly position the single tooth through selection for the tooth position, which facilitates more comprehensive analysis.

The invention discloses an Alzheimer's disease image classification method based on a multi-modal nerve image, and the method comprises the steps: firstly constructing a multi-modal Alzheimer's disease image data set which comprises a magnetic resonance imaging image and a tomography image, and carrying out the preprocessing of the images; secondly, a fusion framework based on a ResNet encoder and a gating dynamic Transform decoder is constructed, a modal feature difference recognition and fusion module, a gating multi-head self-attention module and dynamic Tanh activation are integrated, and an Alzheimer's disease multi-modal image classification neural network model is obtained. And finally, training the image classification neural network model through a training set in the image data set, and evaluating the performance by using a test set. According to the method, through explicit modeling modal difference separability and fusion representation alignability, cross-modal cooperation is enhanced, noise interference is effectively suppressed in the fusion process, information fidelity is kept, and accurate and efficient image classification is carried out.

The invention discloses a cultural relic restoration decision-making method and system based on computer three-dimensional modeling, and relates to the technical field of cultural relic restoration, and the method comprises the following steps: building a unified time baseline, generating a phase reference field, introducing a double-frequency comb interference structure to reconstruct a humidity refraction field, locking a zero-phase anchor point, and forming an initial constraint condition of a scanning path; under an initial constraint condition, an airflow phase gradient is obtained by adopting a Schlenn pilot frequency chromatography method, a nonlinear diffraction nucleus is calculated, and a refraction residual spectrum is output for modeling correction. According to the method, humidity disturbance is recognized through interference measurement and chromatography, real-time compensation is achieved in combination with phase sheath and humidity control, the crack and material characteristics are fused through neural field modeling, the solidification process is played back in combination with a mineralization mechanism, and the three-dimensional modeling precision and the restoration decision scientificity are improved.

The invention provides an intraoperative real-time navigation system based on digital twinning, and relates to the technical field of digital twinning, and the system comprises a data collection module which is used for obtaining the three-dimensional form data of a liver and a biliary tract through an intraoperative ultrasonic imaging device, and collecting the elastic modulus distribution parameters of liver parenchyma and a bile duct wall; the construction registration module is used for constructing a real-time digital twin in the liver and gall area based on the three-dimensional form data and the elastic modulus distribution parameters, and carrying out multi-mode non-rigid registration on the digital twin and the liver surface topography and the vascular structure which are subjected to optical coherence tomography in the operation; therefore, a dynamic space mapping relation between the organ structure and the image data is established. According to the method, real-time navigation in the operation is realized through digital twinning, the obstacle avoidance path is updated, and the safety and efficiency in the operation are improved.

The invention discloses a plastic mold injection molding defect detection method and system, and the method comprises the following steps: collecting a surface image corresponding to a plastic mold injection molding part and an internal tomography image, carrying out the denoising, graying and image alignment, and meanwhile, generating a multi-dimensional image data set corresponding to each injection molding part through an associated index; extracting geometric features and texture features corresponding to each injection molding part based on the multi-dimensional image data set, and fusing the geometric features and the texture features to generate geometric texture vectors; performing similarity judgment estimation based on the geometric texture vector corresponding to each injection molding part and a preset defect-free injection molding part feature template, recursively determining a suspected defect area of each injection molding part, and estimating and generating an injection molding part defect type parameter table; and analyzing and generating injection molding part process defect optimization suggestions based on the injection molding part defect parameter table, and meanwhile, carrying out associated storage to generate an injection molding defect detection archive library. According to the invention, the mold cavity position corresponding to the defect can be positioned, and the mold injection molding defect detection efficiency can be greatly improved.

The invention provides a micro-damage tomography method based on a nonlinear ultrasonic static component damage index, and particularly relates to the technical field of material monitoring. The method specifically comprises the following steps: S1, arranging sensors on the surface of a to-be-detected component; s2, setting a signal excitation end and a signal receiving end; s3, signal emission is carried out on the signal excitation end, a receiving signal of the signal receiving end is collected, and error preprocessing is carried out on the collected signal; s4, carrying out fast Fourier transform analysis and obtaining a static component energy value; s5, calculating a nonlinear damage index; s6, based on a detection grid formed by a circular array or an orthogonal scanning type array, a nonlinear damage index is used as a parameter to be embedded into an RAPID ellipse positioning algorithm, pixel values of the detection grid in an imaging area are calculated and filled, and a micro-damage tomographic image is generated. According to the method, millimeter-level positioning imaging of microcracks, layering defects and the like in the to-be-monitored structure can be realized by combining the nonlinear damage index with the RAPID ellipse chromatography algorithm.

The invention provides a stratigraphic structure and ground pressure distribution detection method based on wave velocity tomography, and relates to the technical field of wave velocity tomography. The method comprises the following steps: firstly, arranging dense linear detector arrays in a monitoring area at an interval of 5m, and collecting the distribution condition of an aquifer, a lithology detection result and a drill core diagram of the monitoring area; recording seismic wave data, carrying out noise reduction processing on the seismic wave data, picking up arrival time, and associating the arrival time with a waveform event; performing path tracking on an observation result by adopting a wave velocity inversion algorithm, generating a wave velocity tomography image and substituting the wave velocity tomography image into the wave velocity-ground pressure evaluation model; and finally generating a ground pressure distribution diagram.

The invention discloses an underground coal mine goaf gap space sensing method based on a multiple detection technology, and the method comprises the steps: obtaining a three-dimensional dielectric constant body through a ground penetrating radar, and determining the space position of a goaf gap; resistivity tomography is carried out through the optimally arranged electrode network, and a three-dimensional resistivity body is inverted; constructing a three-dimensional wave velocity body by adopting sound wave detection, and identifying a velocity low-value region; a dielectric constant body, a resistivity body and a wave velocity body obtained by the three technologies are uniformly registered to a cubic grid with a preset resolution and normalized, a caving zone void probability body is constructed by adopting adaptive weighted fusion based on information entropy and a Bayesian maximum posteriori estimation framework, and finally a three-dimensional void model is generated and the total volume is calculated. Through multi-source data fusion of ground penetrating radar, resistivity tomography and sound wave detection, the limitation of a single technology in goaf space detection is solved, the precision of gap detection is improved, and the method is suitable for goaf space perception and treatment.

The invention relates to the technical field of SAR (Synthetic Aperture Radar) remote sensing imaging, in particular to a scattering heuristic SAR tomography method for structured three-dimensional reconstruction, which comprises the following steps of: S1, acquiring and preprocessing multi-baseline SAR data; s2, inverting scattering parameters based on an attribute scattering center model and orthogonal matching pursuit; s3, segmenting a building area according to coherence and morphological indication; s4, combining direction perception expansion with region updating, determining a continuous scattering region, and giving reference height prior; and S5, constructing a regional adaptive dictionary, sparsely solving the elevation and geocoding to generate a structured point cloud. According to the method, physical prior and regional statistics are cooperated, geometric continuity and anti-noise robustness are improved, pseudo peaks and calculation redundancy are reduced, and upgrading from sparse point cloud to a structured model is realized.

The invention relates to the field of low-altitude monitoring and target identification, and discloses a dynamic target detection method based on a three-dimensional low-altitude monitoring radar. The method comprises the following steps: performing three-dimensional scanning to obtain low-altitude echoes, and resolving three-dimensional coordinates of a target based on Doppler frequency shift and array angle measurement; clutters are suppressed by adopting space-time adaptive processing and constant false alarm rate detection; separating real echo and mirror image interference by using a sparse reconstruction method; fine classification of dynamic targets such as an unmanned aerial vehicle is realized through micro-Doppler features; judging abnormity in combination with trajectory entropy and divergence, and correcting refraction errors by using atmospheric stratification imaging; and further identifying a group cooperation behavior based on graph clustering and a speed consistency index, and outputting multi-level layered early warning information. Compared with the prior art, a closed-loop link from single-target detection to group situation analysis is realized, high reliability, anti-interference performance and pre-warning capability are realized, and the detection precision and situation awareness level in a complex low-altitude environment can be remarkably improved.

Systems and methods for compensating for tilt of an intraocular lens (IOL) and systems and methods for adjusting an IOL are disclosed herein. For example, one of the methods may include capturing one or more optical coherence tomography (OCT) images of a subject's eye while implanting the IOL within the subject's eye. The method may further include generating a fixation target such that the fixation target is visible to an eye of the subject; and moving the fixation target until the lateral plane of the IOL is perpendicular or substantially perpendicular to the optical axis of the ophthalmic system. The method may also include directing a laser beam generated by a laser of the ophthalmic system at the IOL.

The invention discloses a glass-based circuit board defect detection method and system, and relates to the technical field of glass substrate defect detection.The method comprises the steps that an optical coherence tomography system with the fixed scanning resolution of 320 * 320 is used for collecting a tomographic image of a target area, three-dimensional reconstruction is conducted on the tomographic image, and a three-dimensional body data model is obtained; extracting a plurality of three-dimensional morphological characteristics such as defect depth, transverse distribution profile and defect internal refractive index unevenness from the model; and inputting the features into a defect classifier constructed based on a three-dimensional convolutional neural network for identification, and performing spatial position verification in combination with a known design layout to generate a final detection report. According to the method, the standardization of the detection process is realized through the fixed scanning resolution, and the efficiency and the result consistency are improved; by quantifying the refractive index non-uniformity in the defect, the optical property variation type defect in the material is effectively identified, and the detection depth and accuracy are enhanced.

The invention discloses a multi-element hydrological information prediction method and system. The method comprises the following steps: acquiring water level, flow velocity, flow and temperature time sequence data of a target water area through a high-frequency acoustic tomography system, and constructing a multivariate hydrological data set containing sampling duration and hydrological parameter vectors at all moments; preprocessing the collected multivariate hydrological data set to generate preprocessed data, and extracting timestamp features of a sequence; and decomposing the preprocessed data into a plurality of intrinsic mode functions and the like by adopting a variational mode decomposition method. The problems of gradient disappearance and local dependence of a traditional RNN model are solved, redundant noise interference is effectively eliminated while the multi-time-scale characteristic of hydrological variables is reserved, the prediction generalization ability under the complex coupling relation is improved, and high-precision technical support is provided for dynamic planning of water resources and disaster early warning.