18results about How to "Solve access difficulties" patented technology

The invention relates to the technical field of lithium battery charging and discharging management, and discloses a lithium battery charging and discharging detection and management method, device and equipment and a storage medium, and the method comprises the steps: carrying out the data collection of the charging and discharging process of a lithium battery pack, applying consistent Gaussian noise, and obtaining an electrode-level expansion data set and a battery-level expansion data set; performing feature mapping and feature mixing by minimizing the maximum average difference loss function to obtain a mapping feature vector; estimating the state of charge and the state of health of the battery through a fusion model of a recurrent neural network and a physical information hybrid neural network to obtain a state of charge estimated value and a state of health estimated value; and constructing a battery pack electric heating model of the lithium battery pack, and generating a corresponding charging and discharging control instruction sequence. Self-adaptive adjustment can be carried out according to the real-time state of the battery, potential safety hazards such as over-charging and over-discharging and out-of-control temperature are effectively avoided, and the use safety of the battery pack is remarkably improved.

The invention discloses a hypersonic flight vehicle adaptive attitude control method based on near-end strategy optimization, and belongs to the technical field of hypersonic flight vehicle control, and the method comprises the steps: building an air-breathing hypersonic flight vehicle longitudinal dynamic model considering power; performing reinforcement learning training on the obtained environment model by using a PPO algorithm to obtain an optimized control strategy; selecting a proper state representation and action space, and designing a strategy network and a value network for the processed model, so that an original complex attitude control problem is converted into a reinforcement learning problem which can be effectively learned; and training the reinforcement learning model by using an improved PPO algorithm to obtain a final control instruction. According to the method, the model is trained by using the PPO algorithm, so that the defects of complex controller design, strict requirement on model precision and the like of a traditional control method can be effectively overcome. A simulation experiment verifies that pitch angle tracking can be effectively realized, and the stability of an execution mechanism is guaranteed.

The invention discloses a thromboembolism occurrence risk assessment method and assessment system. The method comprises the following steps: acquiring a blood vessel image map of a to-be-assessed patient; inputting the blood vessel image map of the patient to be assessed into a pre-trained risk assessment model; wherein the pre-training of the risk assessment model is based on a ResNet-50 model, and self-supervised contrast learning iteration is carried out by inputting positive and negative samples so as to update model parameters; extracting a feature embedding vector in the blood vessel image; according to the feature embedding vector, calculating probability distribution of embolism occurrence risk levels through a model classification head; and according to the probability distribution, selecting a risk level label and outputting the risk level label as an evaluation result. According to the method based on the time axis symmetry, the image data of the patient is collected before and after the embolism occurrence time point, the positive and negative sample pairs are generated, the problem that the embolism sample is difficult to obtain is solved, and meanwhile the sample collection cost is reduced through self-supervised learning.

The invention discloses a lithium battery health state evaluation method and system based on charging data, and relates to the field of lithium battery safety management, and the method comprises the steps: collecting the historical battery replacement data of a lithium battery, and adaptively selecting a part of charging fragments; constructing a battery health state evaluation model, determining network structure parameters of the battery health state evaluation model by using an optimization algorithm, and carrying out transfer learning; and based on the partial charging fragments and the battery health state evaluation model after transfer learning, realizing accurate evaluation of the lithium battery health state. According to the method, the randomness and uncertainty of the charging behavior of the user are effectively dealt with by utilizing incremental capacity analysis and self-adaptive selection of the charging voltage fragment, and the problem that data of different types of batteries are difficult to acquire is effectively solved through transfer learning, so that accurate evaluation of the health state of the lithium battery is realized; rationality and safety management of use of the lithium battery are improved, and safety accidents such as thermal runaway are effectively avoided.

The invention discloses a sound signal noise reduction method and system based on feature fusion. The method comprises the following steps: S1, collecting an actually measured noise signal and constructing a simulated target signal; s2, respectively constructing feature vectors of the actually measured noise signal and the simulated target signal based on features of the actually measured noise signal and the simulated target signal; s3, based on the feature vectors of the actually measured noise signal and the simulated target signal, constructing a fusion feature vector of the simulated sound signal; s4, inputting the fusion feature vector of the simulated sound signal into a multilayer perceptron for training to obtain a trained multilayer perceptron model; and S5, carrying out transfer learning on the trained multi-layer perceptron model to realize actually measured sound signal denoising. Effective training of the multi-layer perceptron is realized by adopting actually measured sound signals and simulated target signals; through transfer learning of a multi-layer perceptron model, under the condition that an actually measured target signal cannot be obtained, noise reduction processing of the actually measured sound signal is realized.

The application discloses a method and system for strengthening main grid elements considering renewable energy under extreme weather, and mainly relates to the technical field of renewable energy research. The method comprises the following steps: collecting an expected value of system loss load caused by extreme weather, and establishing a first objective function with the minimum expected value; modeling an operation mode of a main grid; establishing a linear programming model for calculating a worst probability distribution of uncertain variables; establishing a three-layer mixed integer linear programming model according to the first objective function and the modeling of the operation mode of the main grid; and solving the three-layer mixed integer linear programming model and the linear programming model of the worst probability distribution and outputting a result. The application has the beneficial effects of solving the problem of difficult information acquisition, reducing the difficulty of information provided by a power grid operator, and improving the efficiency of power transmission grid restoration.

The present application relates to a kind of heart ultrasound video semantic segmentation pseudo-label generation method based on optical flow guide, belong to computer vision and medical image processing field.The method includes: selecting two key frames in heart ultrasound video frame sequence, and obtaining the segmentation mask of two key frames by artificial labeling;Optical flow model is fine-tuned using two key frames, the frame between two key frames, the frame of first key frame left side preset quantity and the frame of second key frame right side preset quantity;Based on the fine-tuned optical flow model, the forward optical flow sequence from first key frame to second key frame and the reverse optical flow sequence from second key frame to first key frame are predicted;Based on forward optical flow sequence and reverse optical flow sequence, generate forward propagation mask sequence and reverse propagation mask sequence, and carry out position weighted fusion, obtain the pseudo-label of unlabelled frame.The technical problem that the present application aims to solve is that the label of heart ultrasound video semantic segmentation is difficult to obtain and the quality of pseudo-label obtained is poor.

This invention belongs to the field of liquid level measurement technology for containers or pipelines containing highly radioactive media, and relates to an ionization chamber type liquid level detection device suitable for various highly radioactive media. The device includes a multi-electrode ionization chamber detector, a collimating shield, and a pre-processing unit. This invention guides the radiation emitted by the highly radioactive media into the housing through multiple collimating windows. This ionizes the inert gas in each detection sensitive area, generating charged particles. The high-voltage electric field in each detection sensitive area drives the particles to move to the corresponding collecting electrode. The collecting electrode captures the charged particles and generates an ionization signal, which is sent to the pre-processing unit. The pre-processing unit determines the liquid level height of the corresponding highly radioactive media based on the varying ionization strength signals generated by the ionized inert gas caused by the different radiation intensity emitted by the various highly radioactive media. This allows for the simultaneous identification and location of multiple coexisting highly radioactive media under non-contact conditions.

The present invention discloses a method and system for reducing noise of acoustic signals based on feature fusion, the method comprising: S1: collecting measured noise signals and constructing simulated target signals; S2: constructing feature vectors of the measured noise signals and the simulated target signals based on the features of the measured noise signals and the simulated target signals respectively; S3: constructing a fused feature vector of the simulated acoustic signal based on the feature vectors of the measured noise signals and the simulated target signals; S4: inputting the fused feature vector of the simulated acoustic signal into a multilayer perceptron for training to obtain a trained multilayer perceptron model; S5: performing transfer learning on the trained multilayer perceptron model to achieve denoising of the measured acoustic signals. The present invention adopts measured acoustic signals and simulated target signals to achieve effective training of the multilayer perceptron; through transfer learning of the multilayer perceptron model, when the measured target signal cannot be obtained, the noise reduction processing of the measured acoustic signal is achieved.

The application provides a flexible direct current line frequency variable parameter identification method and system, belongs to the parameter identification technical field of power grid transmission lines, and changes the number and state of equivalent redundant sub-modules input by each bridge arm; according to the number and state of the input half-bridge sub-modules, a voltage characteristic signal of a direct current line is injected; according to the injected voltage characteristic signal, in combination with a mathematical model of a distributed parameter transmission line, characteristic impedance, propagation constant and attenuation constant corresponding to the frequency of the injected voltage characteristic signal are calculated; and according to the characteristic impedance at different frequencies calculated by injecting voltage characteristic signals at different frequencies for multiple times, the characteristic impedance in the full frequency domain is fitted. The application solves the problem that parameters are difficult to obtain due to the absence of a stable fundamental frequency in a direct current system, and improves the frequency variable parameter identification precision of the flexible direct current line.

The adjustable multi-layer high-depth drawing basket comprises a fixed seat, a guide rail connecting assembly, a connecting seat, a longitudinal beam, a hanging basket main body and a hanging basket connecting piece. Two fixed seats are arranged in parallel on the fixed seat. Two connecting seats are arranged in parallel on the connecting seat and are slidably installed on the two fixed seats through the guide rail connecting assembly. Two longitudinal beams are arranged at intervals at the front and rear ends of the connecting seat, and the upper and lower ends of the longitudinal beam are fixed to the two connecting seats. The longitudinal beam is vertically arranged at intervals and is provided with a plurality of embedded holes. The hanging basket connecting piece is detachably clamped in the embedded hole. The hanging basket main body is hung on the hanging basket connecting piece, and a plurality of hanging basket main bodies are arranged at intervals along the longitudinal beam.

The invention discloses a digital camera color characterization modeling method based on spectral sensitivity optimization, which comprises the following steps of: firstly, shooting a color card by using a digital camera in a known light source environment, estimating the spectral sensitivity of the digital camera, and predicting a response value of a training sample by using the spectral sensitivity; normalizing a predicted response value, expanding the predicted response value by using a polynomial, and constructing a predicted response value of a training sample and a color characterization conversion matrix between three stimuli by using a pseudo-inverse algorithm; and finally, calculating a tristimulus value of the test sample by using the constructed color characterization matrix to obtain a final tristimulus value of the test sample.

The embodiment of the present invention relates to the field of enterprise management technology, and specifically discloses a blockchain-based enterprise management method and system. The embodiment of the present invention determines multiple enterprise R&D products; based on blockchain technology, classifies and stores multiple R&D process models; determines the model requester and performs association analysis; when there is a direct association for use, directly transmits the use to the model requester; when there is no direct association for use, after the indirect feedback is passed, indirectly transmits the use to the model requester. Based on blockchain technology, multiple R&D process models can be classified and stored, and when there is a model R&D request, association analysis can be performed. In different situations, direct use transmission or indirect use transmission can be performed to the model requester, and R&D product models can be classified and stored and effectively managed for use transmission, which can avoid the difficulty in obtaining R&D product models and the risk of leakage of R&D information.

The invention relates to the technical field of camera firmware upgrading, in particular to camera firmware offline upgrading equipment and method. The equipment comprises a built-in power supply assembly, a main controller, a local interaction assembly, a storage medium interface and a communication interface assembly, the built-in power supply assembly is used for supplying power to equipment; the main controller is connected with the built-in power supply assembly; the local interaction assembly is connected with the main controller and is used for providing a local operation interface; the storage medium interface is connected with the main controller and is used for accessing a removable storage medium in which firmware data is stored; the communication interface assembly is in communication connection with the main controller and is used for connecting a camera; the main controller is used for writing firmware data from the storage medium interface into the connected camera through the communication interface component; according to the equipment, independent power supply is achieved through the built-in power supply assembly, an offline operation interface is provided by means of the local interaction assembly, the equipment is suitable for outdoor and after-sales scenes without stable power supply, and the convenience and reliability of firmware upgrading of the camera are improved.

The invention discloses an intelligent display system and method for a company exhibition hall. The method comprises the steps of obtaining a real-time position coordinate sequence of visitors of the company exhibition hall; determining a moving speed vector of the visitor according to the real-time position coordinate sequence; determining a speed interval to which the module value of the moving speed vector belongs; based on the speed interval, information data of the corresponding hierarchy is called from a preset multi-hierarchy information base and displayed on a display terminal of a company exhibition hall, and the information data of different hierarchies in the multi-hierarchy information base have different information densities. According to the method, the moving speed vector of the visitor is used as implicit feedback of a cognitive state, and a self-adaptive coupling mechanism of information density and motion behaviors is constructed, so that a low-density overview is pushed when the visitor quickly passes and high-density details are presented when the visitor stops, the problem that information is difficult to acquire in a dynamic scene is effectively solved, and the information acquisition efficiency is improved. Therefore, the content reaching rate of the intelligent display strategy of the company exhibition hall is improved.

The invention discloses an intelligent identification and classification method for a TAP condensate microscopic image based on deep learning, and relates to the technical field of biomedical image processing and artificial intelligence. A TAP condensate microscopic image data set is constructed and preprocessed, and a deep learning identification model based on a convolutional neural network is constructed; the deep learning recognition model comprises a feature extraction backbone network, an attention mechanism module and a classification output layer, training the deep learning recognition model by using the training set, optimizing model parameters through a loss function, inputting a to-be-detected microscopic image into the trained deep learning recognition model, and outputting the to-be-detected microscopic image. The Label-free TAP condensate recognition method has the advantages that dependence on physical color marking in the prior art is abandoned, the high-dimensional features of the image are automatically extracted through deep learning, and accurate recognition of the Label-free TAP condensate is achieved.

The utility model provides a field test device for bearing capacity and friction force of a foundation, which belongs to the technical field of foundation earthwork and comprises a supporting mechanism comprising a supporting plate, a triangular support fixedly mounted at the bottom of the supporting plate and a driving component arranged at the top of the supporting plate. The auxiliary monitoring mechanism comprises a shell, a spring fixedly installed in an inner cavity of the shell, a movable rod movably arranged in an inner cavity of the spring in a sleeving mode, and a limiting plate fixedly installed at one end of the movable rod. Through the overall compact design of the device, the occupied area of the device is remarkably reduced, so that the device can adapt to a narrow space or complex working conditions adjacent to an existing building, and the problem that a traditional test device is limited in installation and operation is solved; meanwhile, real-time visual monitoring of foundation displacement and load change is achieved through the synergistic effect of the auxiliary monitoring mechanism, data acquisition difficulty caused by device structure shielding or insufficient observation means is avoided, and therefore test precision and efficiency are improved.

The invention discloses a method and system for simulating electrocardiogram data generation. According to the characteristics that each waveform signal of a single cardiac cycle is similar to a sine wave or a sharp wave, a mathematical model of each waveform is designed, and then the specific parameters of each waveform are determined according to the characteristics of the electrocardiogram data to be simulated. The mathematical model is combined with the specific parameters to obtain a specific graph of each waveform, and the specific images of each waveform are connected to obtain the electrocardiogram of each cardiac cycle. The entire electrocardiogram data or electrocardiogram can be obtained by connecting the electrocardiograms of all cardiac cycles in sequence. The sine wave is a signal with the singlest frequency component, and any complex signal can be regarded as a composite of many sine waves with different frequencies and sizes. Therefore, the specific parameters of each waveform of the electrocardiogram data to be simulated and the data model can be used to simulate arbitrarily complex electrocardiogram data, thereby solving the problem of difficulty in obtaining electrocardiogram data. The electrocardiogram data generated by the data model can be close to reality.