106results about How to "Avoid redundancy" patented technology

The invention provides a rainfall monitoring method and system based on unmanned aerial vehicle multi-mode noise reduction in the technical field of environment monitoring and unmanned aerial vehicle application, and the method comprises the steps: S1, collecting a visible light image and a long-wave infrared image through a multispectral vision module after an unmanned aerial vehicle takes off, and collecting a rainfall audio from an acoustic cabin through a microphone; s2, carrying out noise reduction processing on the visible light image, the long-wave infrared image and the rainfall audio; s3, extracting a raindrop size distribution histogram and a spatial density thermodynamic diagram based on the visible light image and the long-wave infrared image, and extracting acoustic MFCC features based on rainfall audio; s4, performing feature fusion operation based on the raindrop size distribution histogram, the visual density thermodynamic diagram and the acoustic MFCC features to obtain rainfall intensity; and S5, carrying out cumulant dynamic compensation based on the rainfall intensity to obtain the cumulative rainfall. The rainfall monitoring method has the advantages that the precision, robustness and practical level of rainfall monitoring are greatly improved.

The invention discloses a two-stage multi-mode bearing fault diagnosis method based on a pre-training large model, and belongs to the technical field of bearing fault diagnosis. The method aims at solving the problems that a traditional method is poor in generalization and poor in robustness under multiple working conditions and small sample conditions. The method comprises the following steps: firstly, constructing a learnable multi-modal Tokens which comprises a multi-scale patch Token, a feature Token and a fault Token, and realizing efficient extraction and fusion of multi-modal features; a time-frequency semantic fusion module is introduced, and comprehensive time-frequency features are output through adaptive frequency coding, time coding and multi-modal fusion; and inputting the multi-modal feature sequence into a pre-training BERT model, and adopting a two-stage training strategy, in the first stage, performing self-supervised pre-training by taking mask signal reconstruction as a target, and in the second stage, performing parameter fine tuning by taking fault classification as a target. According to the method, the diagnosis accuracy and the cross-working-condition generalization ability under the small sample condition can be remarkably improved.

The present invention provides surgical instruments configured to engage with bone anchor assemblies to provide modular platforms for performing various steps of surgical procedures, such as spinal rod reduction and counterrotation. For example, in one embodiment, the surgical instrument may include an outer sleeve terminating in a pair of extensions, an inner sleeve having a proximal threaded portion and a distal translational portion and configured to pass through the outer sleeve, and a pair of pivoting arms received in the extensions of the outer sleeve. These pivoting arms may be configured to extend into a channel in the outer sleeve to engage the bone anchor to the outer sleeve, and the proximal end portion of the outer sleeve may include one or more flat portions configured to engage with another instrument.

The application belongs to the technical field of positioning and measurement, and particularly relates to a target positioning method and device combining CSI coarse positioning and Y-type CCD fine correction, which comprises the following steps: S1, CSI acquisition equipment is arranged in a target area, and CSI data between a sending end and a receiving end is acquired; S2, a Y-type CCD sensor is geometrically calibrated and a coordinate system is corrected, and coordinate reconstruction is completed; S3, the CSI data is preprocessed, noise is removed, and input is normalized; S4, time domain features of the CSI are extracted by using a time domain branch; S5, frequency domain features of the CSI are extracted by using a frequency domain branch; S6, a gating fusion module is used to fuse the time domain and frequency domain features, and the approximate position coordinates of a target are output; S7, the Y-type CCD sensor is controlled to optically acquire a target area, and point light source coordinate information is acquired; and S8, error correction is performed on the data acquired by the Y-type CCD, and the accurate position coordinates of the target are output.

The embodiment of the invention provides a method and equipment for determining a power system configuration scheme and a medium. The method comprises the following steps: determining the initial inertia of a system; if the initial inertia of the system is smaller than the inertia demand value, the reactive response capability of each new energy node is calculated, and a first node is determined; if the first node is different from the previous configuration scheme, taking a new energy node of which the short-circuit ratio is smaller than a short-circuit ratio threshold value as a second node after simulating to carry out network construction type transformation on the first node; determining a current configuration scheme and a corresponding configuration cost; after the second node is simulated to be subjected to synchronous phase modifier configuration, the initial inertia of the system is determined again, and the step of judging whether the initial inertia of the system is larger than or equal to the inertia demand value or not is executed again; and if the first node is the same as the previous configuration scheme, selecting the scheme with the lowest configuration cost. According to the scheme, various configuration schemes of the new energy power system can be determined, the scheme with the lowest cost is selected as the target configuration scheme, and the economical efficiency of system transformation is guaranteed.

This application relates to the field of battery technology, and more particularly to a battery management component and battery pack. The battery management component includes a battery management module, which comprises: a BDU component, the BDU component including a housing and a relay module, the relay module being located within the housing; and a BMS slave board assembly, located above the BDU component along the height direction of the battery pack. The BMS slave board assembly includes a BMS cover and a slave circuit board, the BMS cover being disposed on the housing, and a cavity being formed between the BMS cover and the housing, with the slave circuit board located within the cavity. This application is beneficial for improving the energy density of the battery pack.

This invention relates to the field of medical image processing technology, specifically to an automatic segmentation and recognition method and system for cancer images based on the fusion of multimodal images. The method includes: acquiring a multimodal medical image set containing computed tomography (CT) images, magnetic resonance imaging (MRI) images, and positron emission tomography (PET) images; generating spatially aligned data blocks through three-dimensional spatial registration and voxel alignment; extracting fusion features using an improved encoder-decoder network optimized based on the characteristics and spatial dependencies of different modal channels; obtaining enhanced semantic feature maps through multi-level context-aware processing; identifying suspected cancer regions through a region candidate generation network; and simultaneously outputting pixel-level segmentation masks and cancer type probabilities through a segmentation network, ultimately generating a three-dimensional segmentation and recognition result. This method can accurately capture multimodal-specific features, clearly distinguish the boundaries between lesions and normal tissue, simplify the processing flow, reduce errors, and achieve accurate and efficient segmentation and recognition of cancer lesions.

The invention provides a test case generation method and system based on multi-modal machine learning and dynamic optimization, and the method comprises the steps: carrying out the cross-modal feature association of a demand semantic text, a source code instruction stream and a historical defect event record in a software test scene, generating a multi-modal association feature space, inputting a dynamic attention alignment network, and carrying out the multi-modal feature association. Weight distribution is carried out on the business rule semantic dependency relationship, the code execution path dependency relationship and the defect propagation link association relationship, a joint representation vector is generated, double-task cooperative training of test case generation and defect positioning prediction is executed on the joint representation vector, feature extraction weights of double tasks are adjusted to generate a test case generation parameter set, and the test case generation parameter set is subjected to defect positioning prediction. Inputting the boundary test scene into a generator of the generative adversarial network, strengthening feature expression of the boundary test scene, generating a boundary test case set, performing priority ranking on the boundary test case set to calculate case coverage weight, and generating a target test case set. According to the invention, the effectiveness and comprehensiveness of the test case and the utilization efficiency of test resources are improved.

Embodiments of the present specification disclose a multi-granularity graph contrast learning method, device, equipment, medium and program product. The method comprises: using a granule enhancement method to adaptively refine an original graph to generate a plurality of target granules; the original graph is composed of a plurality of nodes and edges representing the interaction relationship between the nodes; the target granule represents a multi-granularity homogeneous region composed of at least Z nodes in the original graph; Z is a positive integer greater than 1; a positive sample pair and a negative sample pair are constructed based on a plurality of target granules; the positive sample pair is composed of nodes in the same target granule in the original graph; the negative sample pair is composed of nodes in different target granules in the original graph; a contrast loss is determined based on the positive sample pair and the negative sample pair; and an initial vector of each node in the original graph is optimized based on the contrast loss to obtain a target vector corresponding to each of the plurality of nodes.

The application provides a road surface state recognition method and device, and solves the problems of single road surface state recognition category, coarse result granularity and inability to distinguish specific road surface abnormal types caused by dependence on simple threshold judgment and shallow features in the prior art. The method comprises the following steps: acquiring a vertical vibration acceleration data segment of a vehicle in operation; extracting a characteristic value according to a preset optimal feature subset, wherein the subset comprises a frequency domain peak value and a spectrum energy; inputting the characteristic value into a classification model to obtain a recognition result, wherein the model is obtained by training based on data comprising at least three road surface state labels. Through fixed feature optimization, the application realizes fine recognition of multiple states such as well frame difference, expansion joint and deceleration strip, and significantly improves the calculation efficiency while ensuring the accuracy.

The application discloses a kind of knowledge embedding and retrieval method and system of multi-modal PDF document, specifically relates to knowledge embedding and retrieval field, the present application uses multi-modal big model identification picture, table and other non-text elements in PDF, generates its position coordinate, converts picture into structured literal description and stores source URL;Second, the original text, picture description and URL are integrated into Markdown format, then, adopt the strategy of gradual blocking: each picture information is individually used as text block, and the remaining pure text is blocked according to character length;Subsequently, all text blocks are vector embedded, and the type is stored as metadata into vector database;Finally, in the retrieval stage, relevant text blocks are returned based on vector similarity;In the generation stage, single mode or multi-modal model generates accurate answer using text content and picture URL.

This application provides a multi-scale island and reef remote sensing image mosaic mapping method, which can be applied to the fields of geographic information science and remote sensing big data processing technology. The method includes: acquiring island and reef image files corresponding to each island and reef in a target area; the island and reef image files are high-resolution remote sensing images that have undergone cloud removal processing and are cropped according to a buffer distance, with the geometric center of the island and reef as the reference; based on the spatial display scale corresponding to the buffer distance, stitching together the island and reef image files of all islands and reefs in the target area to generate an image mosaic map; generating a vector index map that corresponds one-to-one with the geometric position of the image mosaic map, the vector index map containing island and reef identification information of the corresponding geometric position of the island and reef; and superimposing the vector index map onto a predetermined area of ​​the image mosaic map to generate a standardized island and reef thematic map of the target area. This application also provides a multi-scale island and reef remote sensing image mosaic mapping device, equipment, and storage medium.

The utility model discloses a wire coil binding structure for a small animal exercise physiological parameter monitor, which comprises a storage box, the surface of the storage box is fixedly connected with the monitor, the inner wall of the storage box is rotatably connected with a rotating tube, the inner wall of the storage box is provided with a conductive slip ring and a power connection end, and the power connection end is connected with the rotating tube. The front end of the power connection end is electrically connected with a power supply circuit of the monitor, a power line is wound around the surface of the rotating pipe, and a sliding rail is fixedly connected to the top of the storage box through bolts. The L-shaped block drives the rack to move, so that the gear drives the first bevel gear to rotate through the shaft rod, then the first bevel gear drives the rotating pipe to rotate through the second bevel gear and winds the power line, the power line of the parameter monitor can be properly wound, redundant power lines can be collected into the storage box, and the power line can be conveniently stored. Therefore, power line redundancy of the parameter monitor in actual use is avoided.

The image non-uniformity correction method and device, the infrared image device and the computer readable storage medium provided by the embodiments of the present application, the method comprises: acquiring a same group of in-focus images and out-of-focus images collected for a target scene; respectively decomposing the in-focus images and the out-of-focus images through wavelet transform to obtain corresponding in-focus sub-band images and out-of-focus sub-band images; determining a fixed image noise component contained in a high-frequency component in the out-of-focus sub-band images based on the high-frequency component; determining a corresponding image component estimation value according to a sub-band coefficient of the in-focus sub-band images and the corresponding fixed image noise component; reconstructing the image component estimation value through inverse wavelet transform to obtain a non-uniformity corrected image of the target scene, thus avoiding information loss and redundancy of the image signal in the decomposition process, so that the non-uniformity corrected image of the target scene is obtained more quickly and more clearly.

This invention discloses an experimental water tank device for investigating changes in sand ripples on a near-bottom high-concentration sediment bed. The device includes a water storage tank, a straight-channel experimental water tank, and a sedimentation tank. The two sides of the straight-channel experimental water tank are connected to the water storage tank and the sedimentation tank, respectively. A transparent glass panel is installed on the surface of the straight-channel experimental water tank. A trolley track is fixedly installed at the upper end of the straight-channel experimental water tank, and a trolley is mounted on the track. A measuring mechanism is installed on the trolley, and a rangefinder is installed in the middle of the trolley. A flow meter is installed on one side of the trolley, and a 3D scanner is installed on the other side. The 3D scanner is installed on the lower end of the trolley's platform, with its scanning probe facing outwards and tilted downwards. A high-definition camera is positioned on the outside of the transparent glass panel. The measuring mechanism establishes a data transmission connection with a data terminal via a wiring harness. This invention features simple and quick assembly, high automation and efficiency, and the ability to continuously collect data on changes in sand ripples on the sediment bed surface in multiple dimensions.

The application discloses a data acquisition method and device, electronic equipment and storage medium. The method comprises: acquiring audio to be processed collected through a microphone array, the audio to be processed comprising multiple sentences of multi-channel audio; for each sentence of multi-channel audio, acquiring a phase difference feature between at least one group of specified channel audio as target data, the specified channel audio comprising at least two position-associated channel audios. For each sentence of multi-channel audio, the method performs phase difference calculation by incorporating the audio of at least two position-associated microphone channels, which can generate higher-dimensional phase information coverage on one hand, so that the DOA feature obtained after phase difference is more intensive, thereby helping to improve the accuracy of the DOA encoding result; on the other hand, since the position-associated microphone channel audio is used for phase difference calculation, data redundancy can be avoided, thereby helping to improve the efficiency of DOA encoding.

This utility model discloses a thermal management system suitable for containerized energy storage systems, comprising an air conditioning refrigerant circuit and a battery thermal management circuit, both of which include plate heat exchangers. Through this structure, the integration of the air conditioning refrigerant circuit and the battery thermal management circuit reduces system complexity and cost, while also reducing space requirements and maintenance costs. The battery thermal management system utilizes the plate heat exchanger to form a heat exchange with the air conditioning refrigerant circuit, effectively dissipating the heat absorbed from the energy storage battery module through the air conditioning system. The air conditioning refrigerant circuit dynamically adjusts the refrigerant distribution to regulate the heat exchange distribution between the air conditioning refrigerant circuit and the battery thermal management circuit. The battery thermal management circuit includes a phase change thermal storage unit connected in parallel with the plate heat exchanger, releasing stored heat / cold energy during charging and discharging intervals, reducing the frequent start-stop of the compressor and PTC heater.

The invention relates to a process equipment model selection method, device and equipment for ship block manufacturing and a medium. According to the method, production demand prediction, site current situation analysis, production takt extraction, process equipment parameter analysis and cost dynamic evaluation and score screening can be carried out, so that the whole process scientization and datamation of equipment model selection are realized, the process equipment demand of the shipyard segmented manufacturing process can be accurately matched, the production layout is optimized, and the production efficiency is improved. Equipment redundancy or insufficient performance is avoided, cutting and manufacturing precision and efficiency are improved, production capacity is improved fundamentally, energy consumption and maintenance cost are reduced, and product quality stability is enhanced. By accurately matching process equipment and production requirements and optimizing the production process, the segmented manufacturing production capacity and production efficiency can be improved, the production cost can be reduced, the stability of the product quality is improved, the process equipment with high intelligent and automatic degree is introduced, and upgrading and updating of the shipyard production technology are promoted.

The present application takes the position closed structure and the orthogonal component difference as the core, converts the information to be processed into the residual structure representation under the background reference state constraint, the background reference state is constructed by the receiving and transmitting parties according to the consistent generation rule, and can be used as the structural key or the key derivation reference in the safe scene, so that the transmission and storage load can be concentrated on the residual field and the necessary auxiliary field. The framework uniformly carries the encoding, compression, encryption, inversion, decoding and structured domain calculation and topological consistency reasoning, realizes the integration of compression and encryption, storage and calculation. The system improves the equivalent storage density and energy efficiency performance through structured aggregation, and provides consistent logical pointing and calculation basis for reconstruction and reasoning.

The application relates to the technical field of power system data analysis and artificial intelligence, and discloses a decision target and multi-source heterogeneous data auxiliary decision report generation method and system; the generation method realizes the automatic generation of the power auxiliary decision report through decision target driven information dimension analysis, multi-source text standardization processing, long text global semantic coding, key information screening, small sample driven optimization and structured rule mapping; the extraction result is highly matched with specific decision targets such as dispatching and fault disposal, and the decision adaptability is strong; the method can be migrated across scenes with few labeled samples, has strong generalization ability, and has low adaptation iteration cost; in combination with secondary error correction and semantic filtering, the method effectively resists the interference caused by oralization and non-standard format, is stable in extraction precision, retains the cross-paragraph correlation information in the long text through semantic blocking and cross-block attention fusion, and significantly improves the efficiency of power text analysis and the objectivity and timeliness of the decision report.

The application relates to the technical field of testing, and discloses a test method for an application system, which comprises the following steps: acquiring a system configuration file, a local application program package and a corresponding local Java bytecode file of a local application system, and determining a target full-amount corresponding relationship of the local application system; acquiring different Java bytecode files of different versions of application program packages, and determining a program difference list; acquiring an outbound configuration file, and combining the target full-amount corresponding relationship and the program difference list to determine a first full-amount test range of the local application system and a plurality of second full-amount test ranges of a plurality of other application systems, and then testing the application system to obtain a target test result of the application system, which realizes bidirectional accurate analysis of a test range of a local program change on itself and other systems and of other system changes on the local system, comprehensively covers transaction interface and business function test requirements among multiple systems in an enterprise, and guarantees the overall operation stability of the application system.

The application belongs to the technical field of automobiles and discloses a front windshield lower decorative plate and an automobile, which comprise a front windshield lower decorative plate body and a side shielding plate which is detachably installed on the side of the front windshield lower decorative plate body and covers the exposed area of a sheet metal gutter assembly. The side shielding plate comprises a hard rubber part and a soft rubber part. The hard rubber part is shaped according to the contour of the exposed area of the sheet metal, and the soft rubber part is arranged on the circumferential edge of the hard rubber part and is attached to the adjacent automobile body part. The application aims to solve the problems of insufficient shielding caused by the exposed joint of the front windshield lower decorative plate and the sheet metal gutter assembly and poor sealing caused by the direct exposure of the joint gap between the two, improve the overall appearance of the front compartment area, and prevent dust and water vapor from the outside from entering the interior of the front compartment through the gap.

The invention provides a hybrid deep learning automobile sales prediction method fused with multi-source features and application, and belongs to the technical field of hybrid deep learning fused with multi-source features. The method comprises the following steps: 1, inputting subjective evaluation data into a semi-supervised feature generation layer, and extracting features in the subjective evaluation data through a method based on semi-supervised learning feature clustering; 2, inputting static non-time-series data and the subjective evaluation type data and the time series data in the step 1 into a parallel feature extraction layer, and performing feature extraction; 3, performing deep fusion on the output in the step 2, and inputting the merged feature vector into a fusion optimization layer; step 4; and using an Adam optimization algorithm to train the models formed in the steps 1-3. According to the method, combined feature extraction and fusion of non-time-sequence feature mixed data of time sequence features, static attributes and subjective evaluation classes are realized, so that the automobile sales volume prediction precision is optimized.

This invention provides a method and system for road condition data acquisition and analysis based on a commercial vehicle connected driving recorder. The invention utilizes a connected driving recorder, a mandatory standard feature in commercial vehicles, to acquire road images in real time via an image acquisition module and perform preprocessing such as backlight compensation, distortion correction, noise reduction, and effective area cropping. An image recognition module employs a lightweight deep learning and rule-based algorithm to locally identify congestion and traffic accidents. A positioning module acquires latitude and longitude, vehicle speed, and timestamps via GPS / BeiDou dual-mode, achieving precise spatiotemporal binding through timestamp alignment and interpolation compensation. A 4G communication module uploads data using a strategy prioritizing event triggering and supplementing with periodic heartbeats. A data monitoring platform verifies the data, performs 3D deduplication, and then visualizes it on an electronic map. This invention requires no additional hardware, is low-cost, has wide coverage, and strong real-time performance, enabling automatic and precise monitoring of road conditions across the entire area, and is suitable for traffic management and logistics scheduling.

The invention discloses a deformation monitoring and early warning method and system for early warning of slope disasters, and the system comprises a geological grid and mark layout module which is used for dividing grids with different densities according to the height and slope rock-soil layer data and a profile map, determining the three-dimensional coordinates of nodes, and embedding passive acoustic vibration marks; the unmanned aerial vehicle inspection planning module determines the number of unmanned aerial vehicles and generates a flight path and equipment parameters; the multi-modal data acquisition module controls the unmanned aerial vehicle to acquire sound vibration, three-dimensional point cloud and environmental data; the model training module constructs a physical constraint function and takes multi-modal data as an input / output theoretical physical quantity; and the early warning judgment module sets a matching degree interval, determines triggering conditions according to normal, attention and early warning intervals of historical data, starts encryption inspection by three times of attention, and triggers an alarm by single time of early warning. According to the invention, encrypted inspection or early warning can be timely started according to the matching degree interval and the trigger condition, and the accuracy and timeliness of slope safety monitoring are effectively guaranteed.

This invention provides a traffic flow speed prediction method and system based on directed hypergraphs and attention mechanisms, belonging to the field of traffic state prediction technology. Based on directed hypergraphs, it constructs the relationships between nodes in a road network; aggregates directed hyperedge information to characterize the complex spatiotemporal features of the road network; builds an encoder and decoder architecture; integrates an attention mechanism, constructs an attention module, and introduces an improved dense connection structure to enhance the method's accuracy. This invention effectively overcomes the shortcomings of methods based on traditional graph structures, achieves the extraction and fusion of temporal and spatial features, and solves problems such as gradient vanishing in deep neural networks. It is applicable to multi-step traffic flow prediction in real road networks and achieves good prediction accuracy.

This invention relates to a collaborative configuration method and system for regional integrated energy systems that considers source-load fluctuations and high autonomy, belonging to the field of integrated energy system planning technology. It aims to address the problems of existing technologies failing to effectively handle uncertainties on both the source and load sides, the disconnect between planning and operation phases, and the lack of quantitative consideration of system autonomy capabilities. The technical solution includes constructing a multi-energy coupling architecture, modeling source-load uncertainties and generating multiple typical scenarios, establishing an integrated demand response model for electricity, heat, and cooling, designing a two-level stochastic programming model based on scenario analysis, and employing a hybrid optimization strategy for solution. This invention can significantly improve system robustness and reliability, reduce carbon emissions, enhance energy autonomy, optimize economics, and improve the supply-demand balance of multi-energy loads.

The application discloses a data query method and device, electronic equipment and readable storage medium. The method comprises the following steps: after receiving at least one semantic query statement, mapping information of a metadata graph atlas ontology is acquired, wherein the mapping information comprises a mapping relationship between a graph attribute class in the metadata graph atlas ontology for describing a data structure of a target data source and configuration file information of a storage file in the target data source; according to the mapping relationship and a graph attribute class corresponding to the semantic query statement, configuration file information corresponding to the semantic query statement is queried; a target storage file corresponding to the configuration file information is extracted from the target data source; the target storage file is converted into a target data set based on the metadata graph atlas ontology; and semantic calculation is performed on the target data set to obtain a query result corresponding to the semantic query statement. The application solves the technical problem that the number of data islands increases rapidly in the prior art, which leads to excessive management workload of data and reduces data management efficiency.

The application discloses a monitoring point layout optimization method and system based on regional scale nitrogen leaching, and relates to the field of agricultural environmental protection.The method comprises the following steps: acquiring a regional area and regional data; based on the regional data, drawing a slope grade map, a groundwater level grade map and a nitrogen accumulation map of the region respectively; performing pixel-to-pixel alignment, superposition and combination calculation on the slope grade map, the groundwater level grade map and the nitrogen accumulation map of the region to generate a plurality of basic units; under a constraint condition, performing initial layout of monitoring points in each basic unit according to the regional area, an obstacle layer and a preset monitoring point spacing; based on an average distance minimization criterion, constructing a target function of the monitoring points; and based on the target function, optimizing the monitoring points in the initial layout by using a space simulated annealing algorithm to obtain an optimized layout of the monitoring points.The application can improve the monitoring accuracy of regional scale nitrogen leaching and the layout efficiency of monitoring well points.

The invention discloses a link tracking sampling rate adjusting method and device, relates to the technical field of cloud computing and can also be used in the financial field, and the method comprises the following steps: obtaining tracking index data including a tracking sampling rate and index data of a JAVA virtual machine; extracting host name and service name information based on the index data of the JAVA virtual machine; and adjusting the tracking sampling rate corresponding to the corresponding service of the corresponding host based on the index data of the JAVA virtual machine, the tracking sampling rate, the host name and the service name information. Therefore, automatic real-time adjustment of the link tracking sampling rate of the specific service on the specific host is realized, manual intervention is not needed, the labor cost is reduced, and the problem of data redundancy caused by improper setting of the sampling rate is avoided.