15results about How to "Overcome loss" patented technology

The invention provides a capacity attenuation trend prediction method of a low-temperature lithium battery, and relates to the technical field of battery health management and prediction. The capacity fading trend prediction method of the low-temperature lithium battery specifically comprises the following steps of S1, initial data acquisition, S2, feature extraction, S3, hybrid prediction model construction, S4, model training and offline verification, S5, online deployment and dynamic correction, and S6, SOH evaluation and early warning output. A hybrid prediction model is constructed by fusing an electrochemical mechanism and deep learning, so that high-precision prediction and full-life-cycle intelligent health management of lithium battery capacity fading in a low-temperature environment are realized, and the problems of accelerated battery aging and prominent safety risk in an alpine region are effectively solved; early warning and intelligent management of the health state of the battery can be realized, and the service life of the battery under low-temperature application can be prolonged.

The invention discloses a quantum classical mixed image classification method based on group isovariant and delayed aggregation. The method comprises the following steps: lifting a convolution module, inputting a target image, initializing a convolution kernel and rotating the convolution kernel, and carrying out convolution and stacking on the target image to obtain an output image; the group convolution module is used for converting the output image of the convolution module into an image sample and carrying out convolution and reverse remodeling operation to obtain an output image; the group pooling and flattening module is used for carrying out adaptive average pooling on an output image of the group convolution module, compressing the output image into a feature vector and obtaining an output feature vector; the group equivariant quantum feature processing module encodes the feature vectors to quantum bits according to the feature vectors output by the group pooling and flattening module; and the delay aggregation and output module measures the quantum bits, aggregates and classifies measurement results, and completes classification of target images. The method provided by the invention has strong nonlinear feature fusion capability, and can realize more accurate image classification.

The invention relates to the field of rolling, and discloses an anti-backlash device, an anti-backlash control method and rolling equipment, the anti-backlash device comprises two bearing seats, a bearing set, a jacking structure and a hydraulic driving part, the two bearing seats are provided with mounting cavities in a penetrating mode in the first direction, one side face of each bearing seat is provided with a containing cavity, and the containing cavities communicate with the mounting cavities; the two ends, in the first direction, of the roller are each provided with a rotating shaft, the rotating shafts are located in the corresponding installation cavities, each installation cavity is internally provided with a bearing set, each bearing set comprises a third bearing, the jacking structure abuts against the third bearing, the hydraulic driving part is in transmission connection with the jacking structure, and the hydraulic driving part drives the jacking structure to abut against the third bearing. The hydraulic driving part drives the jacking structure to continuously and stably apply the pre-tightening force to the third bearing, a thread jackscrew structure which is prone to loosening and losing efficacy is replaced, the problem that the pre-tightening force is attenuated or lost due to vibration and loads is effectively solved, and therefore the anti-backlash effect can be reliably maintained for a long time.

This invention discloses a cross-modal data processing system for the safe operation of hydrogen refueling stations, including a raw data acquisition and processing module, a full-variable safety scanning module, a physical relationship coupling diagnosis module, an adaptive operating condition clustering module, a question-answer pair construction module, a hydrogen refueling station time-series command data acquisition module, and a fault type identification module. By constructing a three-layer semantic enhancement logic and model adaptation strategy, this invention effectively solves the technical problems in the prior art, such as the lack of supervision signals in the raw data of hydrogen refueling stations, the difficulty in identifying hidden faults under complex operating conditions, and the difficulty in adapting heterogeneous feature space models.

The application discloses a multi-modal depth perception and grasping system based on transparent objects, and relates to the field of robot operation, comprising a multi-spectral perception module, a depth correction module, a grasping posture generation module and a control module. The application comprehensively acquires visual information and thermal radiation information of the transparent object by combining two perception methods of RGB-D image and thermal imaging (TIR) image, and analyzes systematic errors of the depth map to detect error sources of the RGB-D camera and the TIR camera. The system adopts an encoder-decoder model as a depth correction core, the model extracts complementary features of the RGB-D image and the TIR image through a modal exclusive encoder, and utilizes a feature fusion module to complete feature alignment and integration, thereby effectively improving the depth estimation accuracy on the transparent surface. Meanwhile, a Bayesian optimization method is adopted to optimize hyperparameters of the depth correction model, through hyperparameter optimization and model fitting processing, the system effectively avoids overfitting and underfitting problems, and further improves the robustness of the depth correction model and the grasping accuracy of the transparent object.

The invention relates to the technical field of image processing, and discloses an operation scene real-time dynamic reconstruction method and system based on three-dimensional Gaussian sputtering. The method comprises the following steps: extracting spatial-temporal characteristics of a soft tissue deformation Gaussian subset through a HexPlane spatial-temporal encoder; fusing the decoded feature vectors to generate a soft tissue deformation parameter set; a deformation field Jacobian matrix of Gaussian elements in the soft tissue deformation Gaussian subset is calculated, a local volume strain rate is obtained through determinant operation, when the strain rate exceeds a preset threshold value, self-adaptive densification operation is executed, and new Gaussian elements inherit parent Gaussian element deformation parameters and are updated to a corresponding set; and combining the updated parameters to carry out probabilistic boundary allocation and transmissivity perception rendering to obtain a reconstruction result. The accuracy, the physical authenticity and the stability of real-time dynamic reconstruction of the operation scene are improved.

This invention discloses a configuration control method for vibratory conveying of bulk materials, belonging to the field of industrial automation configuration control technology. The method includes: constructing a three-dimensional configuration monitoring interface based on the physical characteristics of the bulk material, comprising a virtual vibratory feeder, a virtual conveyor belt, and virtual material level detection points, and embedding an adaptive adjustment module for the excitation frequency; collecting real-time changes in the stacking height through the virtual material level detection points and mapping them to a feeding rate correction coefficient; calling a fuzzy rule inference engine to calculate the target excitation frequency and target amplitude; encapsulating the target parameters into configuration control instructions, and sending them to the programmable logic controller of the physical vibratory feeder for execution through the configuration software data communication interface. This method utilizes virtual material level sensing and fuzzy inference to achieve dynamic tuning of vibration parameters, and improves the real-time performance and reliability of feeding control through a structured instruction encapsulation and verification mechanism.

The present application relates to a kind of training methods of clinical auxiliary diagnosis model, belong to medical information processing technical field, solve the problem of poor coordination of size model in prior art affects the accuracy of diagnosis decision.Method includes: obtaining the medical text of multiple patients and constructs sample set;Text compression model and medical diagnosis large model are constructed, and the pre-training of text compression model and medical diagnosis large model constructed respectively is carried out based on sample set;The parameter of medical diagnosis large model is fixed, and the compressed text output by text compression model is input to medical large model, and text compression model is optimized based on the diagnosis task loss of medical diagnosis large model;The parameter of text compression model is fixed, and the compressed text output by text compression model is input to medical large model, and medical diagnosis large model is fine-tuned based on the diagnosis task loss of medical diagnosis large model, and the trained clinical auxiliary diagnosis model is obtained.The accuracy of diagnosis in complex clinical scenario is improved.

The application relates to the field of artificial intelligence and image processing technology, and discloses a multi-modal large model driven complex scene image data processing method and system. The method obtains target image data, extracts multi-scale semantic features, performs feature coding based on a scene context dependency graph, generates optimized feature representation through attention guided feature fusion and multi-level semantic reasoning, and executes a target processing operation. The application can effectively improve the complex scene image understanding accuracy, enhance the feature expression capability, improve the performance of the model in spatial relationship reasoning and semantic analysis, and is suitable for complex visual scene analysis and decision-making.

The invention discloses a method for preparing a pure phosphorus-containing solution based on purification of sludge gasification slag pickle liquor, and belongs to the technical field of sludge treatment. An acid solvent is added into the sludge gasification slag obtained after ore grinding for dissolution, stirring and acid leaching are conducted, and mixed slurry is obtained; carrying out solid-liquid separation on the mixed slurry, and taking phosphorus-containing supernate; diluting the phosphorus-containing supernate, adding strong acidic cationic resin after dilution, and purifying at normal temperature; when the acid solvent is industrial waste acid, strongly acidic cationic resin is added into the feed liquid obtained after the first purification for secondary adsorption and purification; and after purification, carrying out solid-liquid separation on the obtained feed liquid to obtain a pure phosphorus-containing solution. The purification method provided by the invention is simple in process, good in selectivity and low in phosphorus loss, and provides a high-quality raw material solution guarantee for preparing a phosphorus product with high purity and high additional value from the sludge gasification slag.

The application discloses a method and device for controlling a rolling mill to accurately stop at a strip tail, wherein the method comprises the following steps: obtaining a mark point position of a steel strip; for any mark point in any pass, when the mark point has not left an entry coiler, controlling the entry coiler to track and record position information of the mark point; when the mark point leaves the entry coiler and has not entered an exit coiler, controlling the entry coiler and the exit coiler to synchronously track and record the position information of the mark point; and for any defect point, when the defect point has entered the exit coiler, controlling the entry coiler to clear the position information of the defect point. The application overcomes the situation that the position information of a mark point is lost or inaccurate in the prior art because the position information of the mark point is not tracked in a non-rolling process; effectively improves the reliability of length precision tracking and recording; and realizes accurate stopping at a strip tail in a rolling process.

The application discloses a personal image privacy protection method, system and electronic equipment. The method provided by the application allows a user to specify a certain person in a protected image through language expression, generates multi-scale visual features with sufficient fusion of image and text information by using a lightweight deep neural network to perform parallel coding on input reference information and personal images, generates a stable specified personal privacy protection image mask through a multi-scale feature fusion and mask positioning enhancement module in the decoding process, and in addition, introduces a balanced binary cross-entropy loss to solve the pixel imbalance problem in training, optimize the network performance, and improve the personal image privacy protection effect. The application can solve the problems of excessive protection of content and pixel imbalance in the training of the reference personal image privacy protection network in the existing personal image privacy protection technology.

This invention discloses a method for semantic detection and multi-frame joint signal reconstruction of radar composite interference, belonging to the field of radar signal processing technology. For signal reconstruction, it includes performing short-time Fourier transform and power-law nonlinear transform on mixed and clean interference signals to obtain enhanced time-frequency maps and binary masks; constructing a U-shaped network guided by physical features, embedding two-dimensional constant false alarm rate (CFAR) detection in skip connections, generating a matrix of interference signal-to-noise ratio (SNR), confidence level, and neighborhood interference proportion as physical features, and outputting a semantic mask; using the CLEAN algorithm to suppress interference, and achieving signal reconstruction based on a corrected dictionary; and solving for sparse vectors in the Doppler domain through sparse Bayesian learning to obtain a high-resolution two-dimensional distribution of the target in the range and Doppler domains. This invention improves the accuracy and anti-interference robustness of high-resolution two-dimensional reconstruction of radar targets in the range and Doppler domains through U-shaped network semantic segmentation guided by physical features and sparse Bayesian learning.

The utility model relates to the technical field of alignment film alignment, in particular to a liquid crystal display friction alignment device which comprises a supporting bottom plate, a first triangular block and a second triangular block, a movable frame is arranged above the supporting bottom plate, the inner side of the movable frame is rotatably connected with a friction roller, and the left side of the friction roller is fixedly connected with a connecting rod. The connecting rod is rotationally connected with the movable frame, a first triangular block is fixedly connected to the outer side of the connecting rod, an outer limiting ring is fixedly connected to the left side of the movable frame, and an inner limiting ring is fixedly connected to the left side of the movable frame; when the friction roller is about to rotate due to friction resistance, the connecting rod is driven to rotate reversely through mechanical linkage, the first triangular block is driven to rotate reversely, the plane of the first triangular block makes contact with the plane of the second triangular block, the blocking effect of the second triangular block cannot be overcome through pushing, and the second triangular block cannot move towards the penetrating groove; the interaction limits the reverse rotation stroke of the first triangular block, the first triangular block is forced to stop rotating, and the function of preventing the friction roller from rotating is achieved.

The application relates to the technical field of wireless communication, in particular to a wireless communication system signal sending and receiving method based on an AI model; containing delay coordinate embedding, neural flow tracking, continuous evolution, Riemann decoding and a closed-loop control unit; the system maps pilots to a high-dimensional phase space by using the Takens principle, reconstructs a channel dynamic topology; the core is to calculate a flow field vector by using a manifold derivative network, continuously deduces time by using a neural differential equation, and eliminates evolution deviation by combining a geometric projection correction term, so that future channel states are accurately predicted; a CSI matrix is solved based on the prediction result to optimize beam emission; the application breaks through the limitation of single-variable observation, and realizes reconstruction and perception from discrete data to the whole picture of a high-dimensional nonlinear system.