8results about How to "Simple features" patented technology

The invention relates to a vehicle-mounted radar waveguide antenna structure, which is a waveguide processing piece formed by splicing an upper waveguide processing piece (51) and a lower waveguide processing piece (52) up and down, a first waveguide transmission cavity (1), a waveguide antenna cavity structure, an electromagnetic band gap structure (3) and an electromagnetic band gap avoiding area (4) are arranged in the upper waveguide machining part (51) and the lower waveguide machining part (52). Compared with a conventionally-designed terminal open-circuit waveguide antenna, the vehicle-mounted radar waveguide antenna structure has the advantages that splicing of two layers of waveguide pieces can be achieved, complex waveguide structures are horizontally laid through reasonable design, the distribution characteristics are simplified as much as possible while splicing of the two layers of waveguide pieces is achieved, the machining difficulty is greatly reduced, and the cost is reduced. The cost is reduced while the performance of the commercial vehicle-mounted radar is improved, and the influence of waveguide piece machining errors on the performance can be reduced while the wide impedance bandwidth is kept.

The invention relates to the technical field of industrial working condition recognition, and discloses a blast furnace working condition recognition method and system fusing a process variable and a video image, and the method comprises the steps: carrying out the interpolation processing of the process variable, carrying out the averaging of a video image frame, and aligning the multi-source heterogeneous information to the same time step; thus, multi-source heterogeneous information with inconsistent sampling frequencies is aligned, a deep neural network model jointly driven by process variables and video images is constructed, representative working condition features in the multi-source heterogeneous information are extracted, the problem that working condition information is not completely utilized when only a single information source is used is solved, and the method is suitable for the multi-source heterogeneous information. A double-layer residual error connection module and a model stability evaluation index are designed, and accurate recognition of the working condition of the blast furnace is achieved.

The invention discloses a shale TOC prediction method based on logging data feature derivation and machine learning, and relates to the technical field of shale TOC prediction, and the shale TOC prediction method based on logging data feature derivation and machine learning mainly comprises the steps: obtaining shale TOC data through a rock pyrolysis experiment; according to the shale TOC data, using a geological research tool to obtain original logging data and preprocessing the original logging data; and performing feature derivation on the preprocessed logging data to obtain a new data set, training a random forest machine learning model to obtain a shale TOC prediction model, and predicting shale data to be measured to obtain a shale TOC prediction result. By implementing the shale TOC prediction method based on logging data feature derivation and machine learning provided by the invention, the flexibility, applicability and accuracy of shale TOC prediction can be improved.

The present invention discloses a design and experimental method of a characteristic simulation part of a CMC guide blade blade-edge plate connection area, comprising the following steps: a first step, establishing a full-scale macro model of a CMC turbine guide blade; a second step, obtaining the stress distribution of the CMC turbine guide blade under service conditions; a third step, extracting the high stress area of ​​the CMC turbine guide blade, i.e., the blade-edge plate connection part; a fourth step, establishing a characteristic simulation part; a fifth step, optimizing the design load characteristics to determine the load size and angle direction of the CMC guide blade blade-edge plate connection simulation part; a sixth step, carrying out a high-temperature static strength test of a characteristic simulation part of a CMC turbine guide blade blade-edge plate connection area. The present invention can obtain the bearing capacity size and failure mode type of the connection structure. Compared with the traditional method, the failure behavior of the CMC guide blade blade-edge plate connection structure can be predicted more economically and effectively.

This invention discloses a method and system for predicting the health status of lithium batteries under varying operating conditions. First, key operating condition features such as energy recovery power, energy recovery current, equivalent power, average discharge current, and equivalent current are extracted based on historical battery data, and parameters of a decay relationship model between health status and equivalent cycle count are fitted. Second, a Gaussian process regression model is trained using early data to learn the mapping relationship between operating condition features and decay parameters. Then, by combining real-time monitoring and external information, future energy recovery power, average discharge power, and equivalent power are predicted, and corresponding current feature sequences are derived. Finally, the predicted future operating condition features are input into the trained model to obtain predicted decay parameter values, achieving accurate prediction of future health status. This invention significantly improves the accuracy, adaptability, and foresight of health status prediction under varying operating conditions by integrating battery physical models and data-driven methods and introducing future operating condition prediction.

According to the LOD construction method and device for the GIS large-range live-action model, the nodes are generated through adaptive iterative segmentation in the HLOD tree construction process, the triangular patch data amount of each node is kept within the threshold value range, and the nodes with the too large triangular patch number cannot be generated; meanwhile, the textures of all the nodes are limited to be kept in a similar range, too large textures cannot be generated, and the optimal configuration effect can be achieved in the rendering scheduling process of the result; meanwhile, after the triangular patches in all the nodes are simplified, the texture features in the texture pyramid are merged, and the method can effectively simplify the grids, maintain the features of the grids, reduce the deformation of the textures to the maximum extent, and ensure the visual effect of the grids. In addition, main memory occupation data is stored in a temporary file by using a memory mapping technology, so that the scheme can process large data volume data exceeding computer memory limitation.

The invention provides a method and device for predicting information-credential adaptive migration and electronic equipment, and the method comprises the steps: collecting the research data of an information-credential adaptive migration project, and sorting the research data into a plurality of pieces of sample data; abnormal sample data in the multiple pieces of sample data are cleaned, and cleaned data are obtained; performing feature simplification on the cleaned data through a statistical method of variable dimension reduction and data reduction to obtain simplified features; inputting the simplified features into a credential intelligent evaluation model, predicting the adaptive migration difficulty of the credential adaptive migration project and the number of resources required by adaptive migration, and obtaining a prediction result; the credential intelligent evaluation model is a model pre-constructed based on a machine learning algorithm.

The present invention belongs to the technical field of vehicle collision, and in particular, relates to a simplified analysis and processing method for an AEB braking curve feature, firstly, obtaining a braking curve of a vehicle collision; performing consistency analysis and difference analysis on the obtained braking curve, extracting the braking strategy, braking intensity and time factors in the waveform of the braking curve; then constructing a simplified braking curve model, using the extracted braking strategy, braking intensity and time factors as input data of the simplified braking curve model, and outputting a braking curve stage characteristic diagram; and analyzing the linear change of the braking curve in each braking curve stage characteristic diagram, generating a simplified braking curve of each braking curve stage, and connecting the simplified braking curves of each braking curve stage to generate a simplified characteristic curve of the entire braking curve stage. The present invention can solve the problem of inapplicability of the existing braking curve simplification method.