86 results about "Vector distribution" patented technology

The invention provides a double-pulse high-frequency switching power supply control method and system for precise electroplating, and relates to the field of electroplating, and the method comprises the steps: collecting area surface data through a three-dimensional scanner, and obtaining a three-dimensional model; extracting a high-curvature area grid according to the three-dimensional model, and calculating to obtain a surface concave-convex degree index; performing current field simulation, and calculating current density vector distribution; when the deviation of the current density vector distribution exceeds a preset deviation threshold value, pulse parameters are optimized through a genetic algorithm; selecting a pulse parameter which is most matched with the surface concave-convex degree index, and carrying out iterative calculation to obtain updated current density vector distribution; based on the difference between the updated current density vector distribution and the initial distribution, predicting a coating thickness value, and determining a preliminary evaluation index; and optimizing pulse parameters to obtain a final control scheme of uniform current distribution. According to the method, pulse parameters can be dynamically optimized according to the geometrical shape of the workpiece, and uniform current distribution and stable plating quality are realized.

The invention relates to the technical field of multi-sensor identification, in particular to a coal gangue detection and classification method and system based on multi-sensor fusion discrimination, and the method comprises the following steps: obtaining visible light and infrared images, calculating brightness and intensity judgment feature conditions, executing edge detection to extract gray segments, and fusing textures and a thermal field to generate a vector set. And performing clustering analysis to finish classification judgment, and outputting a coal gangue detection classification result. According to the method, a precise trigger mechanism is established through brightness and thermal radiation double-feature screening, boundary recognition sensitivity is enhanced through gray abrupt change point division, salient region extraction capacity is enhanced through weighted fusion of texture energy and gray gradient, and a cross-modal consistency feature group is constructed through combination of two-dimensional vector construction and similarity screening. The recognition expression integrity is improved, static threshold classification is replaced by vector distribution clustering, accurate mapping and classification decision making of material attributes in a complex scene are achieved, and the stability and the recognition rate of a coal gangue detection result are guaranteed.

The invention relates to the technical field of power electronic device diagnosis, and discloses a reverse conducting IGBT intelligent power module fault automatic diagnosis method and system. The method comprises the following steps: acquiring multi-source monitoring data including a grid voltage waveform, a collector current waveform and a shell temperature change curve when the power module operates; then establishing a dynamic feature extraction model, performing time domain and frequency domain conjoint analysis on the multi-source monitoring data, and generating a feature parameter set; then constructing a fault feature space, and mapping the feature parameter set to a high-dimensional space to form a feature vector distribution diagram; carrying out regional division on the feature vector distribution map by adopting a self-adaptive clustering algorithm, and identifying an abnormal feature aggregation region; and finally, comparing the abnormal feature gathering area with a preset fault feature library through a mode matching engine, and outputting a fault type identification result. According to the method, multi-source data can be integrated to realize dynamic feature extraction and adaptive fault identification, and the real-time performance and accuracy of fault diagnosis are improved.

A method for enhancing detection of morphed biometric modality data is provided that includes receiving, by an electronic device, biometric modality data of a person, extracting feature vectors from the biometric modality data, normalizing the feature vectors, encoding the normalized feature vectors into qubits, and expanding, using at least one quantum algorithm, the normalized feature vectors into a high-dimensional space. Moreover, the method includes generating a distribution from the high-dimensional space based on the qubits, calculating a deviation between the generated distribution and a corresponding record high-dimensionality feature vector distribution of the person, and comparing the calculated deviation against a threshold deviation value. In response to determining the deviation satisfies the threshold deviation value, the method determines the received biometric modality data was morphed.

The invention relates to the technical field of image processing, and discloses a house quality detection method and system based on a live-action three-dimensional model. The method comprises the following steps: converting an OSGB format live-action three-dimensional building model into a body coordinate system and carrying out quality evaluation, carrying out semantic segmentation on a standardized model to obtain a component geographic entity set, establishing an independent local coordinate system of each component to form a single three-dimensional model set, generating a multi-view projection feature image set based on a normal vector distribution planning view angle, and carrying out multi-view projection on the single three-dimensional model set. And detecting defects by adopting a 3D-YOLO-BuildingDefect algorithm, and carrying out inverse transformation to obtain three-dimensional space defect distribution and a quality grade evaluation result. The technical problems that a traditional two-dimensional detection method is insufficient in spatial positioning precision, incomplete in detection coverage rate and insufficient in geometric information utilization are solved, and the spatial positioning accuracy of house quality detection and the comprehensiveness of defect recognition are improved.

The invention provides a multi-source data fusion analysis system for electronic commerce digitization insight, and relates to the technical field of data processing, and the system comprises a reference analysis unit used for selecting a reference analysis unit in a spatial relation structure, calculating fractal dimension features of feature vectors, carrying out multi-level recursive division on the analysis unit based on fractal dimension values, and carrying out multi-level data fusion analysis on the fractal dimension values; each level of division keeps a self-similarity characteristic, and feature partitions are obtained; the partition space distribution module is used for mapping the feature vector distribution to corresponding feature partitions and calculating partition space distribution weights based on vector density distribution and space position relations of the feature partitions; the value evaluation module is used for performing parameter adjustment on the deep learning network by using the partition space distribution weight to obtain a value evaluation result; and the value evaluation module is used for processing a value evaluation result through a multi-modal fusion algorithm, generating a personalized recommendation strategy based on a reinforcement learning framework, and calculating resources and an intelligent routing algorithm so as to complete a digital insight analysis process. The e-commerce data utilization efficiency and the decision-making effect can be improved.

The invention relates to the technical field of data quality evaluation, in particular to an automatic quality evaluation method for a high-quality data set in the cultural field, which comprises the following steps: extracting semantic fragments and vector information, performing clustering analysis on a coverage structure, screening redundant samples, labeling image-text differences, and outputting a consistency evaluation result. According to the method, high-precision recognition of semantic coverage and structure density can be realized through structured extraction of semantic information and vector distribution measurement, and the discriminability of redundancy detection is enhanced through linkage screening of vector coincidence frequency and similarity threshold. The systematicness of image-text consistency marking is improved through an image-text position difference and semantic span combined marking mechanism, and it is ensured that redundant and deviated intersection samples can be accurately recognized through a synchronous contrast mechanism between text screening content and image-text difference marking results. The intensive clustering of the cultural semantic content in the vector space and the quantitative analysis capability of the structure deviation point are synchronously improved, and the comprehensive dimension and logic closure of the evaluation result are optimized.

The invention discloses a power cable outer sheath fault positioning method, and belongs to the technical field of cable fault positioning. Aiming at the problems of poor adaptability, weak anti-interference capability and low positioning precision of the existing cable outer sheath fault positioning technology, the method comprises the following steps of: acquiring horizontal and vertical components of an electromagnetic signal by deploying an array sensor, and obtaining pure vector distribution through Fourier transform and wavelet denoising processing; judging coordinates of an abnormal point according to an amplitude threshold value and a phase ratio, and determining a fault cluster center by adopting K-means clustering; and fusing the environmental data, refining the position through iterative filtering, comparing and confirming a final fault point in combination with triangulation and historical data, and generating a vector distribution map and a diagnosis report. According to the invention, high-precision and anti-interference positioning and visual diagnosis of cable faults in a complex environment are realized.

The invention provides a data security sharing method under an AI platform, and belongs to the technical field of AI platforms, and the method comprises the steps: building a distributed architecture of a confusion center node and a plurality of confusion edge nodes in an AI platform management server, carrying out the knowledge vector extraction of to-be-shared data, and converting the to-be-shared data into a high-dimensional vector for representation; generating a plurality of ellipsoidal confusion bubbles based on vector distribution characteristics and constructing a multi-dimensional authorization strategy, adopting a game boundary model comprising an upper-layer game model and a lower-layer game model to perform separation processing on a crossed and overlapped region, establishing a data training reasoning mapping relation according to a game solving result, and calculating confusion parameters through a confusion intensity optimization function; and finally, real-time confusion protection in the data transmission process is executed, and data flow is continuously monitored. The technical problem of data leakage risk caused by mismatching of a confusion protection strategy and an actual security demand in the data sharing process under the AI platform is solved.

A volume holographic grating, a method for formulating a grating vector distribution formulation thereof, and a method and apparatus for manufacturing the volume holographic grating. The grating vector distribution is estimated by sampling a position of an eye movement range effective region of a plurality of sub-fields of view and a grating vector, matching with Bragg diffraction conditions, of a ray thereof, without considering the diffraction of ineffective rays that ultimately enter beyond the eye movement range, such that most of the effective rays with different incident angles have higher diffraction efficiency on the volume holographic grating, which ensures the overall brightness uniformity of the output beams and extend the field of view.

The invention relates to a vector retrieval method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: receiving a query vector; searching according to the query vector and the global vector index of the vector index based on the search parameter to obtain an initial cluster; wherein the global vector index is determined based on a single-layer hierarchical navigable small-world graph; the search parameters are used for controlling the size of the initial cluster; under the condition that the vector distribution in the initial cluster set does not meet a preset condition, executing expansion search in the global vector index by taking the initial cluster set as a starting point to obtain each adjacent cluster; determining a target cluster set based on the initial cluster set and each adjacent cluster; the target cluster set is searched in a local vector index of the vector index, a target vector is obtained, and the local vector index is determined based on the inverted file plane vector index. By adopting the method, the vector recall precision can be improved.

The application relates to the technical field of power electronic device diagnosis, and discloses a fault automatic diagnosis method and system for an inverse-conducting IGBT intelligent power module. The method comprises the following steps: acquiring multi-source monitoring data of the power module during operation, wherein the multi-source monitoring data comprises a gate voltage waveform, a collector current waveform and a shell temperature change curve; then, a dynamic feature extraction model is established, time domain and frequency domain joint analysis is performed on the multi-source monitoring data, and a feature parameter set is generated; subsequently, a fault feature space is constructed, the feature parameter set is mapped to a high-dimensional space to form a feature vector distribution graph; then, a self-adaptive clustering algorithm is used to divide the feature vector distribution graph into regions, and an abnormal feature aggregation area is identified; finally, a pattern matching engine is used to compare the abnormal feature aggregation area with a preset fault feature library, and a fault type identification result is output. The method can integrate multi-source data to realize dynamic feature extraction and self-adaptive fault identification, and improves the real-time performance and accuracy of fault diagnosis.

The application relates to the field of engineering surveying and mapping technology, in particular to an engineering surveying and mapping marking method and system based on an AI robot, which comprises the following steps: controlling a surveying and mapping robot to move to a to-be-marked engineering area to collect environment point clouds and environment images, constructing a three-dimensional environment map based on the environment point clouds and the environment images, identifying the geometric features and spatial distribution of key surveying and mapping control points based on the three-dimensional environment map, planning a candidate position of a marking point, and generating a preliminary coordinate sequence of the marking point. The application introduces normal vector distribution analysis and a depth compensation mechanism, before surveying and mapping marking spraying, the robot calculates the local flatness and roughness of a base surface through line laser scanning, automatically fits an inclined plane and calculates a compensation depth, simultaneously adjusts the pitch angle of a mechanical arm, so that an inkjet head is always perpendicular to the base surface and is within a depth of field range, which ensures that no matter how the ground fluctuates, the marking point can keep a standard circle and clear boundaries, and solves the problem of difficult marking on uneven ground.

The invention discloses a risk management and control zoning method and system based on multi-medium interactive pollution data, and relates to pollution management and control, and the method comprises the steps: delimiting an initial risk pollution region through random pollution point detection, and determining main pollutants of each medium and the content of the main pollutants; analyzing the content change gradient of the pollution point, and constructing a content reduction vector line; setting a multidirectional edge region, analyzing vector line difference, and if the criterion does not reach the standard, expanding the edge until the criterion is met or crossed; accurately measuring an actual pollution range, extracting geographic features, and establishing a correlation group of pollutants, vector distribution and the geographic features; according to the method, vector distribution, geographic features and pollutants are taken as elements, a multi-medium interactive pollution comparison model is constructed, and real-time data are analyzed, so that the accuracy, dynamic adaptability and real-time response efficiency of multi-medium pollution risk management and control are improved, and efficient partitioning and early warning in a complex terrain scene are supported.

The invention provides a motor control method and device, a vehicle and a storage medium, and the method is applied to the field of vehicles, and comprises the steps: obtaining first to third phase current values of a motor when the motor is in a locked-rotor state, and determining a zero vector adjustment value of the motor according to the first to third phase current values based on a pre-constructed zero vector adjustment distribution table, and adding the zero vector adjustment value to the current three-phase duty ratio to obtain a final three-phase duty ratio of the motor, and then determining a control signal of each phase of bridge arm of the motor based on the final three-phase duty ratio so as to control the motor according to the control signal of each phase of bridge arm. The method can dynamically change the current distribution of each phase of bridge arm of the motor, optimize the loss distribution of a power device, improve the torque output of the system and further improve the locked-rotor capability of the motor by dynamically adjusting the zero vector distribution strategy.

The invention relates to the technical field of motor driving, and discloses a motor driving direction adjusting method and system based on an attitude sensor, and the method comprises the steps: carrying out the motion state analysis of a target vehicle, and obtaining a target operation mode; calculating a zero vector distribution proportion and a vector switching sequence according to the target operation mode; generating a first motor torque instruction and a second motor torque instruction according to the attitude angle data of the target vehicle; and when it is detected that the target operation mode is switched, smooth transition processing is carried out on the zero vector distribution proportion, the vector switching sequence, the first motor torque instruction and the second motor torque instruction, and a PWM control signal is output. The control intention of a rider can be accurately predicted, mode misjudgment and frequent switching are effectively avoided, reliability and continuity of operation mode recognition are ensured, parameter sudden change impact during mode switching is effectively eliminated, and vehicle operation stability and riding comfort are improved.

This invention relates to the field of large-model latent space mapping technology and discloses a cross-scene hazard migration identification method based on large-model latent space mapping. The method collects historical hazard data and normal operation data from multiple scenarios, and obtains a standardized scene dataset after format unification and noise filtering. Then, a large-model latent space mapping module is constructed to map hazard features and operation features from the standardized data to the latent space of a pre-trained large model, generating scene feature latent vectors. Based on these latent vectors, a cross-scene feature alignment model is constructed, obtaining a unified feature representation across scenarios by aligning the differences in latent vector distributions across different scenarios. Next, the hazard migration identification model is trained, using the unified cross-scene feature representation and real-time data from the target scenario to predict the probability of hazard presence. Finally, the scenario-level hazard identification threshold is calculated by combining the probability distribution of historical hazard data from the target scenario, and the feature alignment model parameters are updated periodically.

The application provides a water level regulation method and system for a water conservancy hub. The method includes the following steps: collecting data by underwater robots and satellite remote sensing data simultaneously, constructing a sediment deposition space-time atlas containing a deposition gradient, and periodically correcting the space-time atlas. A radar array is deployed in the curved section of the spillway, and a multi-frequency pulse signal is used to analyze the three-dimensional sediment flow velocity field vector distribution. Through the correlation analysis of the dynamic coupling of the deposition gradient and the flow velocity field, the correlation area of the flow velocity mutation and the sediment deposition is accurately identified, and a constraint condition set containing coordinate positioning and flow-silt matching rules is established. Combined with real-time water level monitoring data, the constraint condition set is used to calculate and generate a dynamic adjustment parameter sequence of the spillway gate opening, and the water level is accurately regulated. The technical scheme provided by the application can accurately regulate the water level of the water conservancy hub by intelligently optimizing the spillway parameters, effectively alleviate the sediment deposition problem in the high-sediment water area, and ensure the safe operation and flood control efficiency of the hub.

The application relates to a speech synthesis model training method, a speech synthesis method, equipment and products. The speech synthesis model training method comprises the following steps: obtaining training speech spectrum information corresponding to a training speech sample of a training speech object; inputting the training speech spectrum information into a first coding module in a speech synthesis model to be trained, obtaining a first coding vector corresponding to the training speech spectrum information through the first coding module, and determining training vector distribution parameters corresponding to the first coding vector; obtaining a training object timbre feature corresponding to the training speech object based on the training vector distribution parameters, obtaining first synthesized speech according to the training object timbre feature and training text information corresponding to the training speech sample; obtaining a first model loss value according to the difference between the first synthesized speech and the training speech sample; and adjusting model parameters according to the first model loss value to obtain a pre-trained speech synthesis model, which can effectively improve the similarity between the timbre of the synthesized speech and the timbre of the speaker.

The application discloses a variable-frequency motor leakage current suppression method, a motor driving control system and a storage medium, relates to the technical field of motor driving control, and the variable-frequency motor leakage current suppression method comprises the steps of: acquiring an actual leakage current value of a variable-frequency motor; determining a target coefficient value of a zero vector distribution coefficient according to the actual leakage current value; the actual leakage current value is positively correlated with the proximity degree of the coefficient value of the zero vector distribution coefficient to the boundary value of a preset coefficient value range; generating a PWM pulse signal according to the target coefficient value and a reference voltage vector of the variable-frequency motor; and controlling the variable-frequency motor to operate according to the PWM pulse signal. The application can conveniently and at low cost realize suppression of the leakage current of the variable-frequency motor.

The present application relates to the technical field of data quality evaluation, in particular to a kind of automatic quality evaluation method of data set, comprising the following steps: extracting semantic fragment and vector information, clustering analysis covering structure, screening redundant sample, marking text difference, output consistency evaluation result.In the present application, the structured extraction and vector distribution measurement of semantic information enable high-precision identification of semantic coverage and structure density, vector overlap frequency and similarity threshold linkage enhance the discriminability of redundant detection, text position difference and semantic span joint labeling mechanism improves the systematicness of text consistency labeling, the synchronous comparison mechanism between text screening content and text difference labeling result ensures that the intersection sample of redundancy and deviation can be accurately identified, the dense clustering of cultural semantic content in vector space and the quantitative analysis ability of structure deviation point are synchronously improved, and the comprehensive dimension and logical closure of evaluation result are realized optimization.

The invention discloses a 3D printing small round hole part forming method which comprises the following steps: a) constructing a three-dimensional digital model of a part, and repairing a part model; b) according to part materials and small round hole structure characteristics, the width of a molten pool of a used metal powder material is included; the number of small circular hole contour laser vectors, the length of a single-section laser vector and the distance between an entity vector and a contour vector are set, a laser vector planning path at the small circular hole is obtained, and contour vector distribution is vector distribution with a staggered starting point and an end point; vector adjustment is carried out on the theoretical contour of the small round hole, a polygonal approximate contour formed by N sections of linear vectors is generated, at least one point of the starting point and the end point of each section of vector deviates from the boundary of the theoretical hole to the interior of a part entity, and a laser opening point and / or a laser closing point are / is located within the edge of the hole; and c) guiding the slices into equipment for printing. Energy accumulation is effectively restrained, hole blockage is avoided, and the precision of fine-structure parts such as small holes formed through 3D printing is improved.

The present disclosure provides a kind of unmanned aerial vehicle route planning method for water and electricity engineering, it is related to water and electricity engineering safety monitoring technical field.The method comprises: generating the three-dimensional terrain grid model corresponding to target operation area, and voxelization processing obtains initial voxel map, determine first candidate waypoint in combination with initial voxel map;Based on the average normal vector distribution of initial voxel map, the voxel unit is segmented and refined to generate fine voxel map, and determine second candidate waypoint in combination with fine voxel map;Collision detection is carried out to all candidate waypoints, to obtain target waypoint set;According to the target waypoint set, unmanned aerial vehicle operation route is generated.The scheme is realized by constructing and optimizing multi-level voxel map, in combination with candidate waypoint screening and spatial collision detection, with lower calculation cost, the unmanned aerial vehicle patrol monitoring route planning that is adapted to complex terrain and covers complete, strong feasibility.

Embodiments of the present application propose an imaging system based on super-Raleigh limit focusing lens and its application, which can be widely applied in the technical fields of photolithography, biomedical, optical imaging and nanometer structure precision measurement; the system can produce transverse wave vector distribution and excitation and detection vector beams with wave vector range meeting the requirements by wave vector ring modulation on incident linearly polarized light, focus the vector beams to make the focusing field meet the scale requirements, so as to obtain super-Raleigh limit excitation PSF and detection PSF, and obtain a confocal PSF capable of exciting high-order terms of spot intensity by superimposing the excitation and detection PSFs, thereby improving the imaging resolution of the system; on the other hand, the system can use solid and hollow focusing spots formed by focusing vector beams to form an image, and calculate according to the imaging result to reduce interference, so as to obtain a high-resolution detection result far exceeding the Raleigh diffraction limit, and further improve the resolution of the imaging system.

The invention relates to a commodity recommendation method and device, equipment and medium in the technical field of e-commerce, and the method comprises the steps: obtaining an interactive commodity sequence corresponding to a user in response to a user recommendation event, and the interactive commodity sequence comprises multi-modal information corresponding to a plurality of target commodities interacting with the user; determining a commodity feature sequence corresponding to the interactive commodity sequence by a multi-modal representation network in a preset commodity recommendation model, wherein the commodity feature sequence comprises a fusion feature vector of multi-modal information of each target commodity; determining a user preference sequence corresponding to the commodity feature sequence by a deep extraction network realized based on a plurality of different preset time windows in a commodity recommendation model, wherein the user preference sequence comprises preference feature vectors of multiple dimensions; and mapping a user preference vector corresponding to the user preference sequence into commodity vector distribution by a fusion classification network in the commodity recommendation model, and determining recommended commodities based on preference probability distribution obtained by mapping. According to the invention, commodities preferred by the user can be accurately recommended.

The application discloses a SVPWM modulation method suitable for a staggered parallel Vienna rectifier and belongs to the technical field of power electronics. The method comprises the following steps: judging a sector where a reference voltage vector is located; selecting a corresponding small vector according to the sector, mapping a three-level space to a two-level space to obtain an equivalent reference voltage vector; adopting a traditional two-level SVPWM algorithm to calculate the action time of the equivalent reference voltage vector; introducing a vector distribution factor k to adjust the action time distribution of two switch states of a specific small vector in each sector; and generating a PWM signal. The application simplifies the calculation complexity of the SVPWM through equivalent two-level mapping, simultaneously realizes unified regulation of midpoint voltage balance and input current zero-crossing distortion by using the vector distribution factor k, effectively improves the input current quality, and reduces total harmonic distortion.

The application discloses a composition automatic scoring method based on multi-stage learning, and the method comprises the following steps: S1, extracting the shallow language features, emotional features and theme relevance features of the composition; S2, theme relevance feature extraction; S3, construction of a beautiful sentence identification model and extraction of composition style features; S4, training of a base learning machine; and S5, composition vector distributed representation and feature fusion model training and prediction. The application is applied to the field of automatic composition scoring, and a comprehensive and multi-dimensional composition scoring feature is designed for Chinese composition scoring, the detection and discovery of beautiful sentences in the composition are realized, and the beauty degree of language expression in the composition is better considered; meanwhile, the composition automatic scoring based on multi-stage learning is proposed, and multi-angle composition features are effectively combined for composition scoring.

The invention discloses a controllable filtering method based on porous material surface performance enhancement, and relates to the technical field of porous material controllable filtering, and the method comprises the following steps: generating an asymmetric liquid bridge evolution mapping graph based on a tension behavior identification matrix on the basis of identifying that a surface active component exists in a liquid, determining whether an asymmetric contact liquid bridge is formed and local wetting offset is caused or not through a three-dimensional contact front edge track, a left-right contact area ratio and tension vector distribution; on the basis of an asymmetric liquid bridge evolution mapping graph, a response offset indication graph is constructed, and whether opening and closing of the membrane hole are out of control or not is recognized by calculating the non-synergy degree among the membrane hole edge wetting response change rate, the liquid bridge contact center offset angle and the leading-in flow speed. The problem that opening and closing of membrane holes are out of control due to asymmetric contact liquid bridges is solved, local wetting deviation recognition and graded dynamic regulation and control are achieved, and the filtering accuracy and the system stability are improved.

The invention discloses a berthing and departing attitude optimization method and system based on model predictive control, and the method comprises the following steps: constructing a ship three-degree-of-freedom nonlinear kinematics and dynamics model, and taking the model as a prediction model of MPC; establishing a target function containing state tracking errors and control energy consumption, and controlling output through real-time rolling optimization calculation under the physical constraints of the thruster thrust and the rudder angle; in the berthing stage, weighted collaborative optimization is conducted on the ship position deviation and the attitude angle deviation through an MPC, and high-precision closed-loop control and thrust vector distribution of the pose in the low-speed environment are achieved; in the off-berthing stage, real-time prediction and momentum attenuation compensation are carried out on the inertial sliding track of the ship by combining MPC prediction step length based on preset off-berthing direction guidance, and output of a propeller is dynamically adjusted to ensure the safe envelope of an off-berthing path. According to the invention, high-precision attitude control and dynamic obstacle avoidance of the ship in a complex limited water area can be realized.