7results about How to "Type fast" patented technology

The invention discloses a cross-temperature health state assessment method and system for an underwater robot battery, and relates to the technical field of battery health state assessment, and the method comprises the steps: S1, collecting data in the operation process of an underwater robot; s2, an environment temperature profile is constructed, and working condition types are identified; s3, constructing a multi-dimensional health feature vector; s4, constructing an LSSVM and SVR regression model, and optimizing model hyper-parameters; s5, calculating characteristic stability and comprehensive complexity indexes, and adaptively selecting a model; s6, identifying the working condition category of the charge-discharge cycle, extracting and standardizing the features, calling the adaptive model, iteratively outputting SOH estimated values, and splicing to form an SOH evolution curve; according to the cross-temperature health state evaluation method and system for the underwater robot battery provided by the invention, the problems of unstable cross-temperature performance and insufficient generalization ability in the prior art are solved.

The invention provides a power grid data restoration method and system based on Huber norm tensor decomposition, and belongs to the technical field of intelligent power grids and high-dimensional data processing. The method comprises the following steps: constructing multi-source and multi-dimensional power grid load data into a high-dimensional tensor structure; a Huber norm-based tensor decomposition model is adopted as a core reconstruction engine, through differential punishment of different residual errors, random noise is effectively suppressed, key abnormal modes such as electricity stealing are reserved, and excessive smoothing of abnormal features by a traditional method is avoided; efficiently solving the low-rank factor matrix of the tensor by using a stochastic optimization algorithm; and finally, realizing accurate filling of massive missing values in the original data through the reconstructed factor matrix. According to the method, the restoration precision and robustness of the power grid data containing noise and abnormal values can be remarkably improved, a high-quality data basis is provided for subsequent advanced analysis tasks such as electricity larceny detection and load prediction, and the method has important practical application value.

The application relates to the technical field of wind tunnel equipment health monitoring and intelligent fault diagnosis, and provides a fault sample generation method based on a frequency domain guided diffusion model under variable working conditions. The method realizes adaptive generation of missing samples under continuous variable working conditions by constructing a working condition guided diffusion generation mechanism, converts a traditional sample completion problem into a working condition condition-oriented distribution learning process, can infer dense continuous missing working condition samples from sparse known working condition samples, and thus provides high authenticity and high fidelity enhanced sample input for a subsequent fault diagnosis model; meanwhile, by combining a frequency domain sliding average denoising strategy, the application can effectively accelerate diffusion model sampling convergence, inhibit generation process fluctuations, and significantly improve the quality and stability of the generated samples.

The invention relates to the technical field of information identification, in particular to a medicine information identification method and system based on AI vision, and the method comprises the following steps: importing a medicine outer package image, adjusting the contrast and brightness of the image, removing background noise, and obtaining a processed image. According to the method, the image of the external package of the medicine is processed, so that the definition of the image is improved, and high-quality input is provided for feature extraction. And after conversion to the gray mode, through analysis and morphological transformation of the convolutional neural network, accurate capture of drug shapes and textures is improved, and more accurate drug category classification is realized. According to the method, the accuracy of medicine identification is effectively improved, particularly the diversity and complexity of medicine processing are excellent, the error rate in medicine distribution is reduced, the problems of wrong distribution, missed distribution and frequent distribution in the medicine distribution process are reduced, and the medicine circulation efficiency is optimized.

The utility model discloses a kind of mine gushing water multi-medium filtering mechanism with high adaptability, it is related to mine gushing water filtering technical field, including base and the fixed connection of its upside middle part supporting plate, the upside of base is fixedly installed with two-stage filter assembly and primary filter assembly side by side, one side of supporting plate is fixedly connected with pressurizing assembly, pressurizing assembly fixedly communicates in two-stage filter assembly and primary filter assembly intermediate position, mine gushing water in the utility model first enters primary filter assembly, quartz sand or anthracite is used as filter medium in primary filter assembly, suspended solids, colloid and organic matter etc. are filtered, the water after first filtration is pressurized and transported to two-stage filter assembly by pressurizing assembly, activated carbon or manganese sand is used as filter medium in two-stage filter assembly, heavy metal ions etc. in it are adsorbed or removed, in practical application, the kind and combination of each stage filter medium can be flexibly adjusted according to specific mine gushing water quality condition, improve the application range of filtration, improve filtration quality.

This invention primarily relates to the field of neural network technology. It discloses a method, device, and medium for recognizing traditional Chinese medicine (TCM) decoction pieces based on dynamic serpentine convolution. The method includes: acquiring an image of TCM decoction pieces and inputting it into a preset feature extraction network, which includes multiple convolutional kernels; adjusting a target convolutional kernel among the multiple convolutional kernels to adaptively align the sampling points of the target convolutional kernel along the meandering geometric contour in the TCM decoction piece image; extracting features from the adaptively aligned meandering geometric contour to obtain target features; classifying and recognizing the target features using a preset classifier, and outputting the recognition result of the TCM decoction piece type. This application effectively solves the problem of mismatch between the fixed geometric structure of standard convolutional kernels and the features of the decoction piece image, thereby significantly improving the recognition accuracy and efficiency of TCM decoction pieces.

This invention relates to an input receiving system and a control method for such an system. After the engine is started, the user can quickly input operating instructions corresponding to the vehicle's interior environment. The input receiving system includes: first and second input receiving devices capable of receiving input of operating instructions for operating an object of the vehicle; and a temperature detection unit for detecting the interior temperature of the vehicle. The first input receiving device includes: a first input receiving unit capable of receiving input based on a pressed or touched operating instruction and including a first display unit capable of displaying information; and a first control unit controlling the action of the operating object based on the input of the operating instruction via the first input receiving unit. The second input receiving device requires a longer start-up time than the first input receiving device. The first control unit displays recommended operating information on the first display unit based on the temperature detected by the temperature detection unit, and performs an operation corresponding to the recommended operating information based on pressing or touching the first display unit.