217results about How to "Achieve refinement" patented technology

The invention provides a power anomaly detection method and system based on multi-mode special collaborative causal thinking chain reasoning, and relates to the technical field of power anomaly detection. Comprising the following steps: acquiring an embedded representation of multi-modal data in power equipment, inputting the embedded representation into a general model, and generating a framework of a causal chain; the power exclusive model is based on a framework of a causal chain, each node of the causal chain is refined layer by layer, detail information is supplemented, key factors are filled, and a causal graph is obtained; inputting the causal graph into a hypergraph neural network, mining high-order association in data through multi-layer convolution operation, and updating embedded representation of nodes in the causal graph to obtain an updated causal graph; and on the basis of the embedded representation of the nodes in the updated causal graph, calculating the potential risk influence of the nodes, and determining abnormal nodes. According to the method, a general model and an electric power exclusive model are combined, efficient and accurate abnormal causal chain reasoning is realized by integrating multi-modal data, and the accuracy and effectiveness of electric power anomaly detection are improved.

The invention provides an unmanned aerial vehicle accessory intelligent identification and access method and system based on a sensor, and relates to the technical field of unmanned aerial vehicle accessory management, and the method comprises the steps: collecting the three-dimensional contour information of unmanned aerial vehicle accessories, generating standard point cloud data, carrying out the feature extraction, and carrying out the feature alignment and interaction, generating a high-dimensional fusion feature matrix of the target unmanned aerial vehicle accessories; based on the feature pyramid network, constructing multi-scale feature representation, generating hierarchical feature descriptors, performing similarity calculation, generating a similarity score matrix, performing optimal matching, establishing an adaptive verification rule base and performing accessory verification; calculating an optimal action sequence of an access path based on model information, mapping the optimal action sequence into a motion track parameter of a mechanical arm, collecting multi-point stress data, predicting the optimal clamping force, establishing an accessory service life prediction model, performing prediction in combination with historical data, and generating an accessory state evaluation report and a maintenance suggestion.

The invention discloses a liquid fertilizer application effect analysis method based on self-supervised learning. The method comprises the following steps: S1, generating initial feature data; s2, environment feature representation is generated based on a heterogeneous environment self-adaption module; s3, extracting short-term and long-term spatio-temporal characteristics of the liquid fertilizer application effect based on the dual spatio-temporal characteristic decoupling and dynamic fusion model, and generating comprehensive spatio-temporal characteristic representation; s4, generating fertilization characteristics in different situations by utilizing self-supervised learning, and eliminating environmental interference factors through a causal reasoning module; s5, generating a fertilization intention feature, and dynamically adjusting a fertilization strategy; s6, when the difference between the prediction result and the actual effect exceeds a threshold value, triggering a re-learning module to update model parameters; and S7, carrying out integrated optimization, realizing feature sharing and task coordination through multi-task collaborative learning, and carrying out automatic tuning by utilizing Bayesian optimization. The intelligent analysis of the liquid fertilizer application effect is realized through the self-supervised learning and multi-task collaborative optimization method.

The invention provides an energy-saving evaluation and operation strategy optimization method for a central air-conditioning system. The method comprises the following steps: firstly, building an Internet of Things platform based on the central air-conditioning system, and monitoring and collecting operation parameters of various equipment in the system in real time; unifying formats and preprocessing operation parameters, uploading the operation parameters to a cloud database for storage, and dividing the operation parameters according to categories; performing mapping modeling on the central air-conditioning system in the energy analysis platform, and performing parameter configuration at the same time; then, the divided data in the cloud database are connected according to evaluation categories, and meanwhile, an extensible formula expert database is introduced to evaluate the running state of the central air conditioning system based on an empirical algorithm, and abnormal strategy reminding is conducted; and prompting to adjust the running state of the equipment according to the strategy. According to the method, the problem of strategy missing is effectively solved through an optimization strategy of the extensible expert experience library; and through analysis and verification of seven functions, integrated, refined and systematic analysis of energy consumption and optimization strategy improvement and advanced management are realized.

The invention relates to the technical field of photovoltaic power station inspection. The invention provides a photovoltaic inspection management method and system based on an unmanned aerial vehicle, and the method comprises the steps: constructing an inspection management database based on historical data; respectively constructing an inspection planning model and a data analysis and evaluation model based on the inspection management database; planning a flight path and an endurance strategy through the inspection planning model, and dynamically optimizing the flight path and the endurance strategy through the inspection planning model according to the real-time data; an inspection task is executed according to the dynamically optimized flight path and the endurance strategy, related data of the photovoltaic power station in the inspection process are collected in real time, and the related data are returned in real time; related data returned in real time is analyzed and evaluated through the data analysis and evaluation model, and corresponding operation and maintenance measures are formulated according to evaluation results, so that the potential problems that an existing inspection mode depends on manual inspection, the efficiency is low, each corner of the photovoltaic power station is difficult to comprehensively cover, and missing is likely to occur are solved.

The invention discloses an intelligent comprehensive management method and system for a safe community, and the method comprises the steps: carrying out the data aggregation and storage through a distributed big data platform for massive community data resources accessed to a unified management platform, extracting key community management indexes and business elements through the operation of data cleaning, correlation analysis and the like, and carrying out the data collection and storage. A command and dispatch-oriented multi-dimensional data model is constructed, and flexible data query and analysis are supported; on the basis of a multi-dimensional data model, a rule-based expert system technology is adopted, experience knowledge and decision logic of managers are subjected to formalized expression, a community management knowledge base and a rule base are constructed, automatic execution of business logic is achieved through a rule engine, and a command and dispatch scheme is dynamically generated according to the real-time state of a community. The problems of information isolated island, low data utilization rate, low commanding and dispatching efficiency and the like in community management are effectively solved, and intelligence and refinement of community management are realized.

The invention provides a slope stability evaluation model construction method considering vegetation influence. The method comprises the following steps: determining vegetation classification; acquiring root morphology of different types of vegetation, and calculating root tensile strength and soil shear strength increment under the action of the root according to the root morphology; obtaining growth speeds of different types of vegetation, and calculating root enhancement factors, soil reinforcement efficiency and vegetation growth cycle influence factors according to the growth speeds; and constructing a slope stability evaluation model according to the root tensile strength, the soil shear strength increment under the action of the root, the root enhancement factor, the soil reinforcement efficiency and the vegetation growth cycle influence factor. By using the model, the slope stability is evaluated by considering the vegetation influence, so that optimization of vegetation selection and configuration is facilitated, the slope protection effect is improved, and the engineering cost is reduced; quantification and refinement of slope stability evaluation can be realized, and a reliable basis is provided for engineering design and construction.

The invention belongs to the technical field of water resource planning and management, and particularly relates to a method for calculating an effective hydrological connectivity strength index range of a wetland based on an InSAR (Interferometric Synthetic Aperture Radar) technology. The calculation method comprises the following steps: acquiring image data of an area to be calculated; identifying all wetland plaques in the water body area; dividing the wetland plaques into different effective hydrological communication type groups; calculating an elastic force value of each wetland patch; constructing a water level fluctuation-ecological elastic force curve under different effective hydrological communication situations, carrying out segmented fitting on the water level fluctuation to generate a fitting line, calculating the mean value of the elastic force of the wetland plaques under the effective hydrological communication type, generating an elastic force mean value line, and calculating the elastic force mean value line; the two intersection points of the elastic force mean value line and the fitting line are the effective hydrological connection strength index range. According to the method, the wetland plaques of different effective hydrological connection type groups are divided according to the difference of the effective hydrological connection strength, the optimal ecosystem elastic force of the wetland plaques is calculated respectively, and then the effective hydrological connection strength index range is determined.

The invention belongs to the technical field of alloy additive materials, and particularly relates to an AlSi10Mg alloy and a laser powder bed melting preparation method thereof, seed crystal alloy powder with the mass percent of Al-2. 63Ti-0.66 C-0.13 B is introduced into the AlSi10Mg alloy for modification, the TM-AlSi10Mg alloy is prepared through the laser powder bed melting technology, and grain refinement and microstructure optimization are remarkably achieved. The TM-AlSi10Mg alloy shows a double-peak heterogeneous microstructure formed by fine isometric crystals and thick isometric crystals which are periodically arranged, and the average grain size is about 2.8 microns. The yield strength, the tensile strength and the ductility of the alloy are all improved.

The invention belongs to the technical field of mechanical control, and particularly discloses and provides a gray fabric carrying and stacking manipulator intelligent control system which comprises a carrying information import module, a gray fabric state monitoring module, a gray fabric environment monitoring module, a carrying setting analysis module, a carrying control analysis module, a database and a gray fabric carrying execution terminal. By integrating a plurality of functional modules, efficient, safe and accurate control over gray fabric carrying is achieved, the carrying information import module collects basic attributes and planned carrying paths of gray fabric, the gray fabric state monitoring module collects gray fabric images, and the gray fabric environment monitoring module monitors the carrying environment; the three jointly provide data support for the carrying setting analysis module so as to judge whether a carrying strategy needs to be adjusted or not. And a new control index is generated through the carrying control analysis module, and finally, an accurate carrying instruction is executed by the gray fabric carrying execution terminal. The series of modules are tightly combined, so that the carrying quality and efficiency are improved.

The invention provides a water and soil loss prediction evaluation method and system, a storage medium and electronic equipment. The method comprises the following steps: constructing a corresponding digital prediction process processing module and a digital prediction parameter database based on a preset prediction process; constructing a data set containing low-resolution DEM data and DOM data and high-resolution DEM data and DOM data, and constructing a water and soil loss prediction model based on the data set; and performing water and soil loss prediction evaluation based on the prediction process processing module, the digital prediction parameter database and the water and soil loss prediction model. According to the method, high-resolution data and conventional-resolution data can be compatible for water and soil loss prediction and evaluation, water and soil loss prediction and water and soil conservation effect evaluation work are refined in space, and the overall evaluation efficiency can be effectively improved.

The invention relates to an operation information prediction method and device based on enterprise project informatization data. The method comprises the steps of obtaining project structured data, project unstructured data and project field standard data of an enterprise project; taking the project field standard data as a causal relationship constraint condition, and constructing a project causal graph of the enterprise project according to the project structured data and the project unstructured data; reasoning the operation information of the enterprise project according to a causal relationship among variables in the project causal graph to obtain operation information reasoning data; and performing causal intervention analysis on the operation information reasoning data to obtain operation information prediction data of the enterprise project. By adopting the method, the adaptive capacity of sudden changes and complex market environments can be effectively improved, so that refinement and intelligentization of project management are realized, and enterprises are promoted to improve the overall operation efficiency and market competitiveness.

The invention belongs to the technical field of electrolytic copper foils, and relates to an additive for an ultralow-profile electrolytic copper foil, an electrolyte, a preparation process of the electrolytic copper foil, the electrolytic copper foil and application of the electrolytic copper foil. The additive comprises a brightening agent, a wetting agent and a leveling agent; the brightening agent is hexylbenzylamine salt, sodium dithiodipropane sulfonate and sodium N, N-dimethyl dithioformamide propane sulfonate; the wetting agent is hydroxyethyl cellulose and polyethylene glycol; and the leveling agent is hydrolyzed collagen. When the electrolyte containing the additive is used for preparing the copper foil, grain refinement of the raw foil and leveling of the outline are realized, and a foundation is laid for realizing the ultralow-outline electrolytic copper foil. And the design of the front section, the middle section and the rear section of the anode plate is combined, an original two-step method is replaced for producing the electrolytic copper foil, equipment is simplified, the production technological process is shortened, and the production cost of the ultra-low-profile electrolytic copper foil is greatly reduced.

The invention provides a remote desktop configuration method and device and electronic equipment, and belongs to the technical field of computers. The method comprises the steps of obtaining employee portrait data, wherein the employee portrait data comprises at least two of basic information, organization information, work content information, work mode information, project participation information and confidential degree information; determining a first target configuration template matched with the employee portrait data based on a preset matching rule; the preset matching rule comprises remote desktop configuration templates corresponding to different employee portrait data; and sending the first target configuration template to a remote desktop server to perform remote desktop configuration based on the first target configuration template. According to the staff portrait data, a plurality of dimension features such as staff departments, work contents, levels, participation items and confidential degrees are comprehensively considered, the staff portrait data with the multi-dimension features are automatically matched with the remote desktop configuration template through the preset matching rule, and refinement, automation and efficiency of remote desktop configuration are achieved.

The invention, which relates to the technical field of travel big data evaluation, discloses a travel big data evaluation system comprising a tourist attraction supporting facility evaluation module, a social media big data evaluation module, a miraculous degree module and a comprehensive scoring module. The invention also discloses a travel big data evaluation method. The method comprises the following steps: collecting scenic spot data; cleaning and standardizing the collected data, and performing hierarchical scoring; analyzing the processed data to generate a comprehensive score; and the generated score and analysis result are fed back to the scenic spot and the travel management department, and optimization suggestions and improvement schemes are provided. According to the invention, on the basis of social media data, the service quality, environmental protection and tourist experience of tourist attractions and cultural projects can be monitored in real time, dynamic feedback is provided through a scientific evaluation system and a big data analysis model, the tourist service quality is improved, the international competitiveness of cultural tourist resources is enhanced, and support is provided for the development of the cultural industry.

The invention relates to the technical field of greening management, in particular to an urban greening state monitoring method and system based on digital mirror image information, and the method comprises the steps: collecting the real-time live-action data of a designated city, combining the real-time operation rule of the city, and generating a virtual city update mirror image through a digital twinborn technology; extracting digital mirror image information in a specified time period from the virtual city updated mirror image to obtain greening state mirror image data, and generating a virtual city greening state by analyzing the mirror image data; further detecting the greening state of the virtual city, generating greening state early warning information, and feeding back the greening state early warning information to the real city to determine a monitoring area and a monitoring index; and performing live-action monitoring on the designated area of the real city, collecting and analyzing monitoring data to obtain an actual monitoring result of the alarm area, and synchronizing the actual monitoring result to the virtual city update mirror image. Dynamic monitoring and bidirectional feedback of the greening state are realized, and technical support is provided for fine management and scientific decision-making of urban greening.

The invention discloses a phenotype analysis method for trees under strong wind stress, which comprises the following steps: a phenotype platform comprises a fan and trees, and the trees are arranged in front of the fan; the laser scanner collects point cloud data of the tree at a certain wind speed; modeling a canopy of the target tree by taking leaf clusters in the point cloud data as units to obtain a crown graphic model, and calculating phenotypic characteristic parameters of each leaf cluster; and calculating wind characteristic parameters in the crown through the k-epsilon turbulence model, the constructed crown graphic model and a numerical solution. According to the invention, the limitation that a conventional wind tunnel experiment is high in cost and small in size and cannot meet the normal scale of an experiment tree is overcome, so that a vivid open wind environment can be reproduced; a method based on a K-epsilon turbulence model special for the forest is proposed to solve wind characteristic parameters in a forest canopy; a digital rubber tree model is reconstructed through a point cloud driving technology, and changes of phenotypic characteristics of an experimental tree under a certain wind speed condition are visually displayed.

The invention relates to a projector heat dissipation and noise reduction method and device, equipment and a storage medium, and the method comprises the steps: obtaining the internal structure data and environment temperature information of a projector, and carrying out the thermal simulation analysis, and obtaining a corresponding thermal distribution diagram; acquiring real-time temperature data of the projector, and performing heat dissipation demand calculation on the real-time temperature data and the heat distribution diagram to obtain a corresponding real-time heat dissipation demand; acquiring light source output data and processor performance data of the projector, and predicting a real-time heat dissipation demand to obtain a corresponding heat dissipation trend; performing heat dissipation planning analysis on the real-time heat dissipation demand and the heat dissipation trend to obtain a corresponding initial heat dissipation control scheme; performing high-temperature identification on the real-time temperature data through a preset nonlinear dynamic model, and performing adjustment in combination with a heat dissipation trend to obtain a corresponding performance adjustment strategy; and analyzing the initial heat dissipation control scheme and the performance adjustment strategy to obtain a corresponding global heat dissipation noise reduction strategy. According to the invention, intelligence and refinement of heat dissipation control of the projector can be realized.

The invention relates to the technical field of riverway desilting, in particular to a riverway self-adaptive desilting system and method based on intelligent water level perception, and the method is executed by a central control unit and comprises the four steps of model construction and benchmark calibration, real-time monitoring and siltation diagnosis, precise survey and operation planning and closed-loop execution and model synchronization. The system comprises a central control unit, a water level intelligent sensing array, terrain scanning equipment and dredging machinery, according to the method, the three-dimensional digital riverbed model is constructed, the sedimentation state is dynamically judged in combination with the water level sensing data, an accurate desilting operation scheme is generated, and operation closed-loop control is achieved. According to the method, navigation and ecological riverway dredging requirements are considered, the dredging precision and automation level are improved, the operation cost is reduced, intelligent transformation of riverway management is promoted, and an efficient solution is provided for long-acting treatment of the riverway.

The present invention discloses a control system and method for alloy additive manufacturing based on laser selective melting, wherein the control system comprises: a laser emission module for outputting laser; a molding chamber, comprising a molding cylinder for manufacturing the required workpiece; and a winding module for providing an alternating magnetic field to the molding cylinder. The present invention provides a solution for grain refinement and strengthening of alloy laser selective melting additive manufacturing based on an alternating magnetic field, which suppresses the texture of aluminum alloy dendrites along the direction of heat diffusion through the composite field effect, blocks epitaxial growth, realizes grain refinement and directional solidification, and thus strengthens the structural properties. The present invention can be widely used in the field of laser melting technology.

The invention discloses a method for preparing a high-purity cobalt solution from cobalt associated with a nickel raw material, which comprises the following steps: pulping the nickel raw material associated with cobalt to obtain pulpified ore pulp; adjusting the pH value of the pulpified ore pulp to 1.5-2.0 by using an acid solution, and carrying out acid leaching reaction to obtain acid leaching slurry; the pH value of the acid leaching slurry is adjusted to 5.2-5.5 through alkali slurry, and a nickel-cobalt extracting solution and filter residues are obtained after precipitation reaction; extracting the nickel-cobalt extracting solution by using a P204 extraction organic phase to obtain nickel-cobalt raffinate; carrying out extraction and reverse extraction on the nickel-cobalt raffinate by utilizing a P507 and C272 synergistic extraction organic phase to obtain cobalt raffinate; and the cobalt raffinate is subjected to extraction and reverse extraction through the P507 extraction organic phase, and the high-purity cobalt solution is obtained. According to the method, the nickel raw material associated with cobalt is sequentially subjected to acid leaching, alkali precipitation, extraction and impurity removal, separation of nickel and cobalt is achieved, the technological process is short, the production cost is low, and refining of the nickel solution and the cobalt solution can be achieved at the same time.

The invention provides a wooden door three-dimensional model parameterization design and numerical control code generation method and system, and relates to the technical field of woodworking numerical control machining and computer vision. A multispectral imaging technology is adopted at a raw material feeding station to obtain a wood board surface multiband image, and a high-definition wood characteristic spectrum is generated through algorithm processing; establishing a mapping rule base of the atlas and numerical control parameters in combination with historical data; the map and the three-dimensional embossment model are superposed, and a tool path and cutting parameters are adaptively adjusted according to texture features to avoid defects and optimize along grains; and finally, numerical control codes matched with wood characteristics are generated, the rotating speed of the main shaft is adjusted according to the hardness, a numerical control machine tool is driven to complete high-precision wooden door machining, and precise numerical control machining based on wood surface characteristic intelligent recognition and self-adaptive adjustment can be achieved.

The invention relates to the technical field of smart tourism, in particular to a personalized scenic spot content generation method, system and device based on a multi-modal knowledge graph and a medium, and the method comprises the steps: collecting multi-modal data of a scenic spot, and constructing a structured multi-modal scenic spot knowledge graph based on the multi-modal data; obtaining personalized data provided by the tourist, and constructing a personalized portrait of the tourist based on the personalized data; in response to an operation of acquiring an image in a scenic spot, identifying the scenery in the image, and extracting a corresponding initial knowledge subset from the multi-modal scenic spot knowledge graph according to an identification result; performing personalized screening and expansion on the knowledge nodes in the initial knowledge subset by calculating the matching degree between the knowledge nodes in the initial knowledge subset and the tourist interest in the personalized portrait of the tourist, and dynamically binding multi-modal resources to generate a personalized knowledge graph; and presenting the personalized knowledge graph. According to the invention, the multi-mode scenic spot knowledge experience of which the structure is matched with the interest and the knowledge background can be provided for tourists.

This invention proposes an ESG-based comprehensive governance assessment method, electronic device, storage medium, and product for shipbuilding enterprises. The method includes: collecting multi-source ESG data and operational data from the shipbuilding enterprise during the assessment period; calculating state baseline parameters based on the operational data according to preset time slices; converting the multi-source ESG data into standard evaluation units and forming ESG vector data corresponding to the preset time slices; matching corresponding ESG assessment parameters from a preset ESG assessment parameter library based on the enterprise size, ship type, or production organization method; if no match is found, adaptively calibrating the ESG assessment parameters to obtain calibrated ESG assessment parameters; calculating governance efficiency indicators for each time slice based on the ESG vector data, state baseline parameters, and ESG assessment parameters; calculating a comprehensive ESG governance efficiency coefficient based on the governance efficiency indicators for each time slice; and obtaining the ESG governance assessment result based on the comprehensive ESG governance efficiency coefficient.

The invention discloses a block chain cross-chain migration-based data processing system and a use method thereof, and the method comprises the steps: responding to a permission configuration instruction of a management object through a permission configuration module, and carrying out the permission setting of specific data through an access control list; determining a data migration mode through a data migration module according to the data type of the to-be-migrated target data; the data migration mode comprises a full migration mode or an incremental migration mode; determining a segmentation strategy of the target data according to the data migration mode through a data segmentation module, and segmenting the target data into data fragments based on the segmentation strategy; and storing the data fragments to nodes on the target chain through a data storage module. According to the method, flexible segmentation is realized through permission configuration, intelligent migration and adaptive determination of the migration mode, refinement, automation and high efficiency of data management are realized, the operation and maintenance cost is reduced, the data security and availability are improved, and the method can be widely applied to the technical field of data processing.

The invention relates to the technical field of intelligent evaluation of garment flatness, and particularly discloses an automatic evaluation method of a non-ironing suit seam flatness grade, and the method comprises the steps: obtaining image data and physical parameter data of a seam region in response to a detection trigger signal of the seam region of a non-ironing suit; and performing key scale screening based on texture contribution degree on the image data, calculating a relevance index between feature distribution and flatness grade probability distribution under different texture scales, and determining the texture scale of which the relevance index meets a preset contribution degree condition as a target key scale. According to the method, the entropy screening mechanism based on the texture contribution degree is introduced, so that the key scale which is most effective for flatness representation can be locked from the multi-source data in a self-adaptive manner, and the refinement and pertinence of feature extraction are realized.

A power plant cable whole life cycle monitoring method based on whole-process identification and mobile terminal code scanning belongs to the technical field of cable monitoring. The method constructs a four-layer architecture of "perception layer-network layer-platform layer-application layer", uses Ecode128 coding of GB / T31866-2023 standard as the unique identification of the cable, and realizes whole-process identification binding by combining two-dimensional code and digital character combination identification carrier. The mobile terminal code scanning is used to realize paperless collection of field data, which is uploaded to the management platform based on the SpringBoot framework through 4G / 5G / Wi-Fi / data line and other transmission modes. The platform adopts front-end and back-end separation design, the back-end integrates SpringMVC and MyBatis-Plus, and the front-end realizes visual display through Vue.js. The function modules of design, construction, operation and maintenance, state monitoring and retirement are developed and designed, and the whole life cycle digital closed-loop management of the cable from design to retirement is realized. The present application effectively solves the technical problems of information dispersion, low efficiency, single monitoring and extensive management in the traditional cable management mode, and significantly improves the fine and intelligent level of cable management.

The application relates to the technical field of chip design, in particular to an AI-based DDR5 memory interface chip adaptive method and system.The method comprises the following steps: obtaining a configuration instruction stream, extracting current and historical configuration instructions, and predicting target pins, switching time and target modes.Before the switching time, target electrical parameters are calculated according to pin electrical characteristics, historical switching records and channel load characteristics.During the switching, the target parameters are loaded and the temporary impedance matching network is switched in.After the switching, a fine-tuning increment is generated according to the deviation of the signal quality and the threshold value, and the updated electrical parameters are obtained by superposition, and the matching network is disconnected after the updated electrical parameters are written back to the register.According to the timing error and the fine-tuning increment generated by multiple switching, the weight parameters are updated and deployed back to the chip.Through AI prediction and the dynamic switching and fine-tuning of the temporary impedance matching network, seamless, stable and low-delay mode switching of the memory interface chip in the reconfigurable computing system is realized.

This invention provides an arc-based additive and subtractive manufacturing method based on interlayer morphology reconstruction, belonging to the technical field of metal additive manufacturing. The method includes depositing an Nth layer of metal material on a substrate to form a deposition layer with a natural wavy morphology; acquiring actual morphology data to identify peak and valley distribution characteristics and planning a subtractive manufacturing path; selectively turning the deposition surface to obtain an anti-wavy substrate; detecting the surface temperature field of the anti-wavy substrate and cooling or preheating the substrate; and repeatedly performing arc-based additive deposition of the N+1th layer on the temperature-controlled anti-wavy substrate to complete the additive manufacturing process. This invention solves the technical problem in existing technologies where the wavy morphology between layers is not addressed, resulting in subsequent deposition layers covering and permanently remaining inside the workpiece, leading to a reduced yield. It achieves the technical effect of suppressing interlayer defects, reducing porosity by 90%, and improving internal quality.

This application discloses an image processing method, apparatus, device, medium, and program product. The method includes: acquiring an initial image containing a target object, and performing pose torsion processing on the target object in the initial image to obtain a pose torsion image; fusing the pose torsion image and the initial image to obtain a fused image; extracting a part image containing a specified portion of the target object from the fused image, and performing image super-resolution processing on the part image to obtain a super-resolution part image; and fusing the super-resolution part image and the fused image to obtain a target image. Using this application embodiment can improve the quality of the target object after pose transfer.