7results about How to "Improve inversion efficiency" patented technology

The application discloses a reservoir intelligent inversion method and related device, relates to the technical field of reservoir intelligent inversion, and comprises the following steps: obtaining multi-source heterogeneous data of a target area and preprocessing; constructing an initial geological model generator based on a conditional diffusion model, and optimizing hidden space parameters in a manner of seismic wave forward simulation; constructing a reservoir knowledge graph and adaptively pretraining and migrating the model online; performing task demand analysis, task decomposition and dynamic collaborative execution on a reservoir modeling task based on a thinking chain technology and a language large model technology, and obtaining iteratively optimized hidden space parameters; inputting the iteratively optimized hidden space parameters into the optimized geological model generator, outputting a three-dimensional distribution model, and extracting a confidence interval feature; incrementally updating the reservoir knowledge graph, determining a reservoir model conforming to a geological mode feature and matching a seismic waveform, and realizing reservoir intelligent inversion. The application can improve the accuracy and efficiency of reservoir inversion.

The invention discloses a sound velocity-density inversion method in quantitative ultrasonic tomography and a related device, and relates to the technical field of medical imaging, and the method comprises the steps: firstly obtaining an original ultrasonic signal collected by the quantitative ultrasonic tomography as a to-be-processed ultrasonic signal, and then carrying out the reconstruction through a delay summation method to obtain an initial reconstruction image; and inputting the two into a sound velocity-density inversion model, and outputting a sound velocity distribution diagram and a density distribution diagram. The model is of a supervised double U-Net architecture and comprises double encoders, double decoders and a cross-path feature fusion unit, the double encoders extract ultrasonic signal physical features and initial image structural features respectively, the double decoders are responsible for reconstruction of two parameters respectively, and the cross-path feature fusion unit achieves feature interaction. According to the scheme, the calculation bottleneck of a traditional physical constraint method is avoided through the double-architecture design, the problem of unstable training is solved through cross-path fusion, the inversion precision, efficiency and stability are finally considered, and the physical consistency of reconstruction results is ensured.

The present specification provides a determination method and device of a multi-task inversion model and a multi-task elastic parameter inversion method. The determination method of the multi-task inversion model comprises: inputting pre-stack seismic data samples into the multi-task inversion model to obtain a plurality of different elastic parameter data; inputting the plurality of different elastic parameter data into a forward model to obtain predicted pre-stack seismic data; determining a pre-stack seismic loss according to the pre-stack seismic data samples and the predicted pre-stack seismic data; determining an elastic parameter loss according to label data corresponding to the plurality of different elastic parameter data and the pre-stack seismic data samples; adjusting parameters of the multi-task inversion model and the forward model according to the pre-stack seismic loss and the elastic parameter loss; wherein the adjusted multi-task inversion model is used to determine a plurality of different target elastic parameter data according to target pre-stack seismic data. The above method can improve the prediction accuracy and efficiency of different elastic parameter data.

This invention discloses a method, device, equipment, and storage medium for geometric correction of hidden road defects based on mechanical drive. The method includes: constructing a finite element simulation sample library for road defects; extracting and fusing multidimensional features from the sample library to obtain a fused feature vector; using this vector to construct a dataset for training to obtain a proxy model for defect parameter inversion; locating abnormal areas of the road medium using 3D ground-penetrating radar and activating the corresponding strain sensor array; acquiring measured strain data and fusing it into a feature vector to be identified; inputting this vector into the proxy model for inversion; and outputting the geometric parameters of hidden road defects. This effectively combines the advantages of 3D ground-penetrating radar and strain sensor arrays, compensating for the shortcomings of single detection methods, and effectively supplementing the inaccuracy of ground-penetrating radar in detecting the boundaries of hidden defects. Through multidimensional feature extraction and fusion and neural network model training, the deep information of strain data is accurately mined, improving the estimation accuracy of geometric parameters of hidden road defects.

This invention relates to the field of bridge structural health monitoring and safety assessment technology, and particularly to a method for detecting the deflection deformation of orthotropic steel bridge decks based on influence surfaces. The method includes: S1, establishing a layered spatiotemporal traffic flow information database specific to the orthotropic steel bridge deck to be tested, generating virtual loads based on time windows and vehicle tail reinforcement coefficients to simulate bridge traffic; S2, acquiring the static stress response of key bridge points when vehicles cross the bridge; S3, inverting the influence surface based on dimensional adaptive prior information, constructing a hybrid likelihood function, and reconstructing a two-dimensional influence surface matrix by integrating typical traffic and tail reinforcement information; S4, comparing the changes and responses before and after the influence surface to infer the deflection deformation. This application can generate virtual loads using traffic flow statistics and invert the entire field influence surface through stress measurement at a single key point; the innovative dimensional adaptive prior setting method significantly improves the inversion efficiency, accuracy, and stability.

This invention discloses a method for decoupling and inverting the emission flow rate and concentration of thermally hazardous gases based on intrinsic orthogonal decomposition, belonging to the field of industrial building ventilation and air pollution control technology. It addresses the pain points of dual-parameter inversion of thermally hazardous gases, such as large sample requirements, low inversion accuracy, and inability to adapt to scenarios with significant disturbances in the flow field caused by pollution sources. This invention constructs a physical model of pollution source diffusion and divides the flow field region. Based on emission parameters and reconstruction error analysis, it determines the optimal deployment area for temperature sensors. Temperature field data is reconstructed through adaptive sampling and intrinsic orthogonal decomposition. The emission flow rate is obtained by matching and optimizing with measured temperatures, and the uniqueness of the inversion results is verified. Simultaneously, based on the actual flow rate obtained through inversion, the emission concentration can be further inverted using the linear proportional relationship of concentration. This invention offers high inversion accuracy and stable, reliable results, suitable for rapid and accurate inversion of thermally hazardous gas emission parameters in industrial scenarios.

This invention discloses a method and apparatus for crack morphology inversion combining full-time step and physical model, comprising: inputting crack height and crack offset in the crack height direction into a physical model; first, processing the crack height through a crack propagation sub-model to output crack geometric parameters for the full-time step; then, processing the crack geometric parameters and crack offset in the crack height direction through a fiber strain response sub-model to output axial strain rate at simulated measurement points for the full-time step; adjusting the axial strain rate at simulated measurement points based on positive and negative strain rate scaling factors; calculating the loss value between the adjusted simulated axial strain rate and the measured axial strain rate; if the loss value is greater than a preset loss threshold, adjusting the corresponding optimization control parameters until the loss value is less than or equal to the preset loss threshold, or a preset iteration stop condition is reached; and outputting the target crack geometric parameters for the full-time step based on the finally adjusted optimization control parameters. This invention can improve the accuracy and efficiency of crack morphology inversion.