46results about How to "Solving Consistency Issues" patented technology

Embodiments of the present application relate to the field of automatic programming, and disclose a data synchronization method and device, electronic equipment and a storage medium. The method comprises: receiving a synchronization instruction input by a user for data synchronization, and generating a data replication message; sending the data replication message to a data synchronization service, and determining whether the data synchronization service receives the data replication message to obtain a first determination result; when the first determination result is that the data synchronization service receives the data replication message, the data synchronization service calls a data replication service; the data replication message is parsed through the data replication service, and each change data in the data replication message is synchronized to each copy database. The technical scheme of the embodiments of the present application solves the technical problems of poor real-time performance and data inconsistency in the data synchronization method in the prior art, and realizes the technical problems of improving the real-time performance of data synchronization and avoiding data inconsistency.

The application discloses a flight control oriented OTA upgrading method, system, device, computer readable storage medium and program product, belongs to the field of computer science and technology, and aims to solve the problems of insufficient safety of an existing upgrading process, unreliable data transmission and weak batch management capability for a heterogeneous architecture. The method establishes a first connection, sends a start request frame containing a specific identification code and an inverse code, sets an upgrading flag and resets the flight control, and disconnects the connection. After resetting, a second connection is established, firmware is transmitted and written, an end request frame with the same frame structure is sent, the flight control is finally reset and starts new firmware, and the connection is disconnected. The frame structure containing the identification code and the inverse code, the instruction code and the check code enhances the communication reliability and the anti-interference capability. The stage resetting and the flag mechanism ensure that the upgrading process is controllable and recoverable, avoids firmware damage or startup failure, and improves the safety and stability of the flight control system remote upgrading.

This invention discloses a two-branch image dehazing method based on edge constraints, comprising the following steps: Step 1: Constructing an image dehazing dataset; Step 2: Obtaining edge maps of the images using the Canny edge detection operator, and constructing a training sample using the edge maps, corresponding fog maps, and clear maps; Step 3: Randomly segmenting the images in the training samples as input to the network, and using data augmentation methods to expand the sample size; Step 4: Constructing a two-branch dehazing network based on edge constraints, including a dehazing subnetwork and an edge subnetwork; Step 5: Initializing network parameters and constructing a target loss function to optimize the parameters of the two-branch dehazing network; Step 6: Using the trained model to dehaze the test fog map to obtain a clear, fog-free image. This invention can utilize edge constraints to recover clear, fog-free images, solving the problem of lost spatial details and semantic inconsistencies in the repaired images during image dehazing tasks.

The application discloses a textile yarn intelligent production control system and method based on digital twinning, which comprises the following steps: S1, obtaining the running data of a spinning frame; S2, establishing a virtual running body of the spinning frame to form a virtual-real working condition state; S3, inputting the virtual-real working condition state into an improved Reformer model, introducing a yarn state neighborhood resonance regularization mechanism in an LSH attention layer, executing neighborhood rearrangement and cross-bar neighborhood splicing, and generating continuous state quantities; S4, adopting a Hilbert-Huang transformation algorithm on the continuous state quantities, introducing a critical precursor stationary phase separation mechanism, and forming multi-scale working condition components; S5, forming a spinning working condition trajectory; S6, executing linkage matching to generate linkage control quantities; and S7, applying the linkage control quantities to the spinning frame to update the virtual-real working condition state. The application can realize continuous modeling and multi-parameter collaborative control of the spinning working condition, and improve the stability of the running state of the spinning frame and the production control precision.

The application discloses a kind of image shadow removal methods of balancing deterministic recovery and perceived quality, comprising:1, first stage global regression analysis is carried out to shadow image, global illumination and color consistency of image are repaired using global regression network based on no residual, and deterministic illumination anchor point is established;2, the output of global regression network is input into the diffusion model of second stage as conditional space prior, and local perceptual refinement is carried out using conditional diffusion model based on block, and fine texture details are recovered by generative prior;3, in the reverse denoising sampling process of second stage, introduce random block overlap mechanism, calculate the mean of all covering block prediction noise as updating basis for the purpose of eliminating the boundary artifact when full resolution inference.The application can significantly improve the visual fidelity of the de-shadowed image while ensuring pixel-level accuracy, and can efficiently process high-resolution images under limited video memory constraints.

The application relates to the technical field of accurate load prediction of a virtual power plant, and provides a load accurate prediction method and system for multi-source heterogeneous data fusion of a virtual power plant, so as to solve the problem that the existing technology is difficult to adapt to the accurate load prediction demand of a virtual power plant for a short period. The application collects photovoltaic output, wind power fluctuation data of a virtual power plant, and real-time current and node voltage monitoring data of a distribution network, associates and labels the former two to obtain an associated data set, phase-calibrates the latter two to obtain a calibrated data set, and integrates the two data sets into a multi-source heterogeneous data set; then, fluctuation characteristics of various data are extracted, an XGBoost algorithm is used to screen out a core information feature set affecting load prediction accuracy, and finally, a GRU time sequence prediction model is used to generate a load prediction result in a preset time period, so that the multi-source heterogeneous data of a virtual power plant can be fused, feature screening and time sequence correlation processing are performed, and accurate load prediction in a preset time period can be realized.

This utility model discloses a blanking and flattening device and operating mechanism, belonging to the field of blanking and flattening technology. The flattening device includes a fixed base, a flattening frame, a pressure mesh, and a driving assembly. The fixed base is located at the bottom of the overall flattening device; the flattening frame is placed on the upper end of the fixed base, with a hollow center, and the pressure mesh is placed within the hollow center and fixedly connected to the flattening frame; the pressure mesh protrudes from the lower end face of the flattening frame; the driving assembly is located on one side of the flattening frame, and its output component is fixedly connected to the flattening frame, enabling the flattening frame to move along the height direction. It can optimize the flattening effect and, when combined with a vision camera and an adsorption device, improve blanking accuracy.

The invention discloses a road marking identifying and spraying method and system based on image processing, and the method comprises the steps: collecting a lane line image through a camera, and converting the lane line image into an aerial view; establishing rigid calibration of the pose relation between the nozzle and the camera to realize coordinate registration; converting the aerial view from an RGB space to an HSV space, introducing a self-adaptive threshold adjustment mechanism on this basis, and obtaining a lane marking area image from the lane line image according to self-adaptive segmentation; a lane image is converted from a pixel coordinate space to a parameter space, and automatic detection of lane edge lines and marked lines is realized through Hough transform; in combination with the detected lane marking area, the detection area is classified through a gray threshold value or a brightness feature, and the offset of a marking center line is calculated; the transverse position of the spraying mechanism is adjusted in real time according to the offset of the center line of the marked line, dynamic opening and closing control over the spraying head is achieved in combination with the vehicle running speed and the recognition signal state, and it can be guaranteed that the spraying track and the recognition center line are kept consistent.

The present application relates to a kind of structure inference, automatic analysis and standardized output of multi-variant BOM table, belong to electronic manufacturing data processing, table analysis and structured data cleaning field.The present application constructs a set of analysis architecture for multi-variant BOM table by the modular processing link of "title row detection-column head normalization-multi-column identification-variant reconstruction-segment cleaning-intelligent inheritance-standardized output", robustly locates complex table head by strong and weak evidence weighting and verification under-probing mechanism, realizes the split and identification of multiple quantity columns using stop mark and semi-finished product number analysis, and introduces cross-row backfilling and position number inheritance rules under paragraph constraint, effectively solves the analysis problem caused by template difference, multi-column variant and information loss, realizes the automation, precision and standardization of BOM data from messy input to engineering level standardized output, significantly reduces manual intervention and improves data quality.

This invention provides a method to improve the consistency of wire-cutting data for large silicon wafers, addressing the problem that existing testing methods cannot provide consistent test data with the wire-cutting direction as the initial position for process debugging and R&D needs. A method is proposed that solves the wire-cutting data consistency problem by changing the initial test position and aligning the test path with the cutting direction, thus facilitating process adjustment and optimization of processing parameters. The initial test angle β is adjusted so that the angle α between the initial test angle and the notch direction is equal to β. The thickness steepness of the test data along the cutting direction is calculated to characterize the impact of cutting on the silicon wafer morphology.

This invention discloses a color paste mixing system, including a color mixing tank, several material tanks, a metering pump, a stirring motor, an output pump, and a three-way solenoid valve, each corresponding to one of the material tanks. The input end of each metering pump is connected to the outlet of the corresponding material tank via a pipe, and the output end of each metering pump is connected to a conveying pipe. The outlet end of the conveying pipe is connected to the inlet of the color mixing tank. The stirring motor is fixedly installed on the top of the color mixing tank, and the output shaft of the stirring motor is connected to the stirring component located in the inner cavity of the color mixing tank.

The application relates to the technical field of financial automation processing, and discloses an archive multi-backup storage device for preventing financial fraud, which comprises a workbench, a conveying belt is installed on the upper side of the workbench, the conveying belt is used for carrying and conveying original bills and pasting sheets, a processing mechanism is used for processing the original bills and the pasting sheets on the conveying belt, a collecting mechanism is used for grabbing the pasted voucher sheets from the conveying belt and placing the pasted voucher sheets in a collecting box, a computer is used for receiving image backup data and electronic data backup generated by the processing mechanism and performing multi-backup data cross inspection, and the computer is electrically connected with the conveying mechanism, the processing mechanism and the collecting mechanism. The application solves the technical problems that the prior art relies on manual operation, is low in efficiency and cannot perform closed-loop checking on final entity vouchers, realizes full-process unmanned operation, and effectively prevents financial fraud.

The application relates to the technical field of data storage, in particular to a sharding archiving and back migration storage method and system using a sorting set mechanism, which comprises the following steps: a CLI receives a command to start various components, carries out configuration periodic archiving and file metadata scanning; interacts with XDFS, stores generated data into a database table, and stores sharding files into a cold storage device to keep a stub in the XDFS; when a gluster client reads a local unarchived file in a volume, sharding metadata {slice number: timestamp} is saved into a set cs-hot-{gfid} of Redis; when an archived file is read and written, corresponding sharding files are downloaded according to file extension attributes and a current read-write offset value. The application provides a low-cost expansion scheme for existing tight storage space; through sharding metadata design, network and CPU resources of the system are minimized; through the design of distributed archiving, maximum throughput performance is obtained.

The application discloses a kind of multi-level man-machine collaborative data labeling method and system based on task ambiguity evaluation, first constructs and trains ambiguity prediction model, utilizes lightweight ambiguity prediction model, predicts the cognitive ambiguity score and logic ambiguity score of each data instance;Four-stage labeling resource pool containing low-performance large language model, high-performance large language model, ordinary crowd sourcing labeler and expert labeler is constructed;According to the predicted two-dimensional ambiguity score, the data instance is automatically routed to the optimal labeling resource by dynamic scheduling strategy, for the task with high cognitive ambiguity, the upgrading mechanism combining crowd sourcing voting and expert arbitration is used, and the final labeled data set is output.The application can intelligently match labeling cost and ability according to the intrinsic properties of the task, significantly reduce the labeling cost and improve the labeling efficiency under the premise of ensuring the data labeling quality, solve the problem of high cost of traditional crowd sourcing and unstable quality of single model labeling.

The invention discloses a mixed loading measurement equipment data acquisition stability method, system, equipment and medium, and relates to the technical field of industrial internet-of-things edge computing, comprising the steps of performing protocol conversion and preprocessing on original data of mixed loading equipment, performing data standardization, analyzing data fluctuation characteristics to evaluate disturbance, and determining the stability of mixed loading equipment data acquisition. Introducing a disturbance shielding mechanism to accumulate and filter historical disturbance, obtaining a shielding quantification result, evaluating a rhythm state by combining the shielding quantification result and a disturbance intensity index, deducing a sampling rhythm adjustment amount of a next period, superposing the adjustment amount with a basic sampling period, and dynamically controlling a data acquisition frequency. According to the method, a complete closed loop from data access to intelligent decision making is formed, and the data acquisition continuity, the system adaptability and the operation reliability of the mixed loading measurement equipment in a complex industrial environment are remarkably improved on the premise that the hardware cost is not greatly increased.

The utility model discloses an elastic glue filling device. The filling device comprises a storage piece, a conveying piece, a conveying channel, a pressure adjusting piece and an air pressure control assembly, the storage part is used for storing elastic glue with compressibility; the conveying part is arranged at the bottom of the material storage part, communicates with the material storage part and is used for pressurizing and outputting the elastic rubber; one end of the conveying channel is connected with the output side of the conveying part, and the other end of the conveying channel is at least partially arranged above the storage part and used for enabling the elastic glue to flow back to the storage part; a filling part is arranged in the middle of the conveying channel and is used for filling and outputting the elastic glue; the pressure adjusting part is arranged at the end, away from the conveying part, of the conveying channel. The air pressure control assembly is connected with the pressure adjusting piece and used for providing constant air pressure for the pressure adjusting piece. Through the arrangement, the perfusion stability and precision of the perfusion device are higher.

The utility model discloses an extruder for a high-hardness plastic grain preparation process, which relates to the technical field of extruders, and comprises an extruder shell, one side of the extruder shell is connected with servo motors which are symmetrically arranged, and the output ends of the servo motors are connected with two groups of screw extrusion components which are symmetrically arranged. The screw extrusion assembly is used for carrying out three-section type conveying, compression, melting and plasticizing treatment on plastic rice raw materials; the screw extrusion assembly comprises a variable-pitch screw connected to the output end of the servo motor, one end of the variable-pitch screw is connected with a variable-diameter screw, and one end of the variable-diameter screw is connected with an equal-pitch equal-diameter screw. According to the utility model, the screw extrusion assembly is arranged and comprises the variable-pitch screw, the variable-diameter screw and the equal-pitch and equal-diameter screw, and gradient propulsion and preliminary loosening pretreatment of plastic rice raw materials are realized by utilizing a gradually-expanded conveying structure of the variable-pitch screw; the problems of raw material slipping, local overheating degradation and insufficient plasticizing caused by a single screw structure of traditional equipment can be solved.

The application discloses an object pose estimation method based on online multi-view fusion, which acquires multi-view continuous image frames and synchronizes camera internal parameters and pose information, obtains two-dimensional boundary boxes, semantic features and confidence through open vocabulary target detection, and then obtains the spatial position, pose orientation and observation confidence of the target by two-dimensional to three-dimensional pose promotion. In a unified coordinate system, multi-constraint target correlation matching based on spatial distance, semantic features and pose difference is performed, and target motion information is estimated according to a historical state to generate a predicted state. An incremental online fusion strategy is adopted to perform weighted fusion on the current observation state, the historical fusion state and the predicted state, and the global target state is updated in real time, and the estimation result containing the target identity, stable three-dimensional pose and motion state is output after repeated target suppression. The method improves the stability and cross-frame consistency of target positioning in a shielding environment and the real-time perception ability in a dynamic scene.

The present application relates to the technical field of crane sling deflection detection. The present application relates to a crane sling deflection detection method based on artificial intelligence. It includes the following steps: S1, build a multi-modal perception array, synchronously collect multi-source perception data, the multi-modal perception array contains an industrial camera, an IMU inertial measurement unit, a cart trolley displacement encoder and a wind speed sensor, which respectively obtain real-time image data of the sling, inertial attitude data of the sling, crane walking motion data and on-site wind field environment data; The present application builds a multi-modal perception array composed of an industrial camera, an IMU inertial measurement unit, a displacement encoder and a wind speed sensor, realizes the synchronous collection of multi-source data of the sling image, inertial attitude, crane motion state and on-site wind field environment, breaks through the limitation of single sensor detection in the prior art, and multiple sensors play their respective roles and complement each other's shortcomings, laying a foundation for subsequent high-precision detection from the data collection level.

This invention relates to the field of lithium battery production control technology, and discloses a production control method for achieving efficient production of lithium battery cells. The method acquires batch characteristic data of lithium battery cells, including electrode material ratio characteristics and electrolyte composition characteristics; extracts a corresponding set of process parameter configurations based on the batch characteristic data; identifies key control nodes in the lithium battery production process based on the set of process parameter configurations, including material ratio adjustment nodes and process parameter switching nodes; calculates parameter deviation data in the production process based on the key control nodes, including cumulative deviations within the same batch and parameter jump values ​​across batches; and extracts a set of reusable process control parameters based on the parameter deviation data, including general process parameters and specific process parameters.

The application discloses a feature alignment fusion method based on structural tensor guidance, and relates to the technical field of target detection, comprising: aligning the spatial size and channel dimension of input features; in a structural tensor representation unit, obtaining main direction information and structural distribution characteristics through gradient calculation, and generating a main direction angle and an anisotropy strength; in a geometric consistency alignment unit, constructing a cross-scale geometric consistency relationship and generating a structural confidence, and combining to form a geometric alignment score; generating a dynamic gating weight in an alignment gating unit, and adaptively calibrating the features through an element-by-element weighting method; and completing multi-scale feature fusion through residual difference interaction and element-by-element fusion operation to obtain fused features. The application fundamentally solves the problems of spatial misplacement and structural inconsistency existing in the existing fusion strategy, especially for dense targets and small target images in a complex background, and improves the retention capability and positioning accuracy of target edge structures.

The invention discloses an intelligent question and answer method, system and device, a storage medium and a program product, and the method comprises the steps: obtaining a question text inputted by a user, carrying out the classification and recognition of the question text, and determining the question classification of the question text; determining a corresponding knowledge base according to the question classification of the question text, and retrieving to obtain knowledge base text information related to the question text; processing and perfecting a user question based on the knowledge base information related to the question text, and analyzing the user question through a language model to obtain an output result; and adjusting an output result according to a question situation or a user demand to obtain a final answer. According to the method, retrieval reply can be carried out in combination with external data, and the text relevancy between reply content and user questions is improved.

The invention discloses a thermal deformation permanent magnet material and a preparation method thereof, the thermal deformation permanent magnet material is prepared from composite magnetic powder through hot pressing densification and thermal deformation, and the composite magnetic powder comprises 55-82 parts by weight of first rapid quenching magnetic powder and 18-45 parts by weight of second rapid quenching magnetic powder; wherein the first rapid quenching magnetic powder is R-Fe-B series magnetic powder, R is at least one of Nd and Pr, and the total atomic percent of rare earth elements in the first rapid quenching magnetic powder is 12.5-15.5 at%; the second rapid quenching magnetic powder is R-Fe-B series magnetic powder, R comprises Nd and at least one of La and Y, and the sum of the atomic percent of La and Y in the second rapid quenching magnetic powder is 1.2-10.0 at%; the first rapid-quenching magnetic powder and the second rapid-quenching magnetic powder are filled in the blank in a partitioned manner in the pressing direction before hot pressing, and the area where the first rapid-quenching magnetic powder is located and the area where the second rapid-quenching magnetic powder is located are sequentially distributed in the pressing direction. The structure uniformity and the performance consistency of the thermal deformation permanent magnet material can be improved.

The application discloses a kind of meridian tire X-ray image disease flaw automatic detection method based on improved YOLO-v5 model, belong to meridian tire detection technical field, including following steps: step 1, meridian tire X-ray image is collected and is segmented processing, uniform resolution, model training sample data are made;Step 2, for the image strip, block missing caused by X-ray machine instability, thereby affecting the detection effect Problem, image restoration processing is carried out;Step 3, design improved YOLO-v5 model, including increasing the fourth detection layer, increase attention module, and improve loss function;Step 4, using meridian tire disease flaw data carries out model training;Step 5, using the model of training completion carries out actual application scene tire disease flaw detection.The application is a kind of automatic detection method, based on improved model can automatically identify multiple disease flaws, and different disease flaws are detected and classified, and detection efficiency and accuracy are higher.

This application provides a method and apparatus for soil moisture data fusion based on Bayesian correction. In the process of fusing multiple soil moisture data products, a Bayesian model with outstanding interpretability is introduced to solve the bias correction problem. On the one hand, it can clearly reveal the interaction mechanism between variables, which helps to understand the causes of systematic bias in multi-source soil moisture products. On the other hand, it can also provide the quantification of the uncertainty of the correction results, which greatly improves the reliability of the data products. In this way, the problems of spatiotemporal inconsistency and physical bias in multi-source remote sensing soil moisture products can be effectively solved, and high-quality soil moisture data products can be obtained.

The disclosure provides a multi-modal fusion encoding method, an encoder training method, a system and an electronic device, wherein the encoding method comprises: inputting a multi-modal description into a preset visual language model to associate features between different modal descriptions; extracting a hidden state of a preset neural network layer in the preset visual language model, and mapping the hidden state to a target space with a preset dimension through a preset projection layer; processing the hidden state of the preset neural network layer after mapping, and outputting a conditional embedding vector for guiding a video generation model to generate a video. The disclosure solves the problem of inconsistent semantics between the video and the input image by jointly encoding different modal data, improves the quality of video generation by matching the dimensions of the input and the diffusion model, and further improves the quality of the video generated by the diffusion model by capturing different levels of semantics to obtain a conditional embedding vector with more abundant information.

The invention relates to the technical field of knowledge graph construction, and discloses a railway disaster knowledge graph intelligent construction method based on a fine tuning Qwen model. The method comprises the steps of performing format unified conversion and deep cleaning on a multi-source railway disaster text to obtain sentence-level corpora, inputting the sentence-level corpora into a Qwen model, performing triple coarse extraction, performing fine tuning training by adopting an LoRA low-rank adaptation method, performing batch reasoning on full-amount corpora, and performing de-duplication standardization according to a minimum editing distance and Jaccard similarity fusion algorithm. And importing a Neo4j graph database to construct a railway disaster knowledge graph. According to the method, the automation degree of railway disaster knowledge graph construction, the knowledge extraction accuracy and the graph structure normalization are improved.

The application provides a system for evaluating the lower limb strength and walking gait of a patient, and relates to the technical field of gait evaluation, comprising a data acquisition module, a synchronous control module and a data processing and analysis module. The data acquisition module comprises an isokinetic muscle strength test unit, a surface electromyography signal acquisition unit and an optical motion capture unit; the synchronous control module is in communication connection with the data acquisition module; the data processing and analysis module is configured to: receive and time-align lower limb muscle strength data, lower limb muscle electrophysiological data and lower limb kinematic data; extract lower limb strength indicators, electromyographic activity indicators and gait parameters from the aligned data; based on the extracted indicators and parameters, establish a correlation model between the lower limb strength indicators, the electromyographic activity indicators and the gait parameters, and output an evaluation result. The application can produce significant effects from data islands to correlation fusion, from subjective experience to objective quantification, and from describing phenomena to revealing causes.

The embodiment of the invention provides a distributed database execution plan acquisition method and device, a medium and a program product, and relates to the technical field of databases. The method comprises the following steps: recording a routing plan of a logic SQL, wherein the routing plan comprises a plurality of data sources and corresponding physical SQL; according to the routing plan, sending an execution plan acquisition request to the plurality of data sources to acquire execution plans of physical SQL corresponding to the plurality of data sources; and carrying out association merging on the routing plan and the execution plans of the plurality of data sources to obtain a unified display result comprising the data source identifiers, the physical SQL and the corresponding execution plans. Based on the unified display result obtained by the method, a user can compare the execution plan of each node through the unified display result, so that the performance bottleneck can be quickly identified, and the efficiency of adjusting and optimizing the performance of the distributed database is improved.

The application discloses a kind of based on degradation perception's fundus image quality enhancement method, system, equipment and medium, wherein method includes: to original low-quality fundus image is standardized pretreatment;To the fundus image after pretreatment is divided into area, feature extraction and degradation degree evaluation, and introduce the self-attention mechanism with degradation perception penalty term, realize differentiation feature enhancement;Build generation network, including encoder and decoder, finally output enhanced fundus image;Build discriminant network, including multiple parallel multi-scale convolution branches, the output of multiple branches is fused, and through double output head respectively outputs true probability value and authenticity confidence heat map;The generation network and discriminant network are trained against;For the fundus image to be enhanced, after image pretreatment and local feature self-adapting enhancement, input trained generation network, output quality enhanced fundus image.The application can realize high-precision, high-fidelity enhancement to low-quality fundus image.