12results about How to "Improve build accuracy" patented technology

The embodiment of the invention provides a verification code file generation method and device, equipment, a medium and a program product, and the verification code file generation method comprises the steps that an editing interface is displayed, in response to a configuration operation for the editing interface, domain knowledge of a target domain is obtained, the editing interface comprises a configuration area and guide information, and the domain knowledge is stored in the target domain; the guide information is used for guiding the front end to input domain knowledge in the configuration area, and the domain knowledge is used for representing a logic rule of a verification task in the target domain; based on the domain knowledge, verification guiding prompt information is constructed, and the verification guiding prompt information is used for guiding generation of a verification code file according to a logic rule; and calling a code generation model, generating a verification code file containing verification logic based on the prompt information, and deploying the verification code file to the target verification platform. Structured domain knowledge is collected through a guide type interface, accurate prompt information is automatically constructed, a verification code file conforming to a domain rule is generated, and the generation accuracy and efficiency are improved.

This invention relates to the field of machine vision and intelligent manufacturing inspection technology, and discloses a visual inspection method for the assembly state of a balance wheel based on multi-view image fusion. The method involves acquiring multi-view images of the balance wheel, extracting rigid body edge feature sets using a multi-scale edge detection operator, generating a spatial compensation matrix based on the linear expansion coefficient and projective geometric invariance, and establishing a three-dimensional spatial coordinate system. It also involves calculating the inner product of multi-view gradient vectors to generate a mask scalar that shields preset spatial points, outputting the target topology network; extracting the non-rigid body displacement time series and obtaining feature accelerations through second derivative calculation, and calculating the deformation compensation vector using the stress relaxation time constant; superimposing the deformation compensation vector onto the three-dimensional spatial coordinate system to drive displacement mapping, generating a three-dimensional model of the target assembly, and outputting defect and assembly tolerance parameters.

Embodiments of the present disclosure disclose a process page display method and device, electronic equipment and a computer readable medium. A specific embodiment of the method comprises: in response to receiving a process page rendering request, obtaining code information and a set of business processing criteria information; generating initial full business process information; verifying the execution relationship between the initial full business process information, obtaining full business process information; rendering the full business process information and rendering and displaying it on the process page; in response to selecting selection information, generating a matching business batch as a first business batch; and displaying the corresponding business process processing tree on the process page. This embodiment can accurately render the corresponding business process information on the process page after receiving the business data related to the business process generation uploaded to the process page, and can set various page filtering operations for the business process information, greatly improving the rendering efficiency of the business process.

This invention discloses a method for constructing a multi-layered assembly of engine room sections and a ship constructed using the same method. The method includes the following steps: S1, manufacturing engine room sections and pre-assembling them off-site to form pre-assembly engine room sections; S2, painting the pre-assembly engine room sections in a painting workshop; S3, transporting the pre-assembly engine room sections and assembling them locally to form the complete engine room section; S4, mounting the complete engine room section onto the ship's hull via a dry dock. This method can reduce manufacturing costs and difficulty. Off-site pre-assembly and integrated painting improve site utilization efficiency. Through simulation prediction, inverted manufacturing of engine room sections and application of reverse pre-compensation can reduce corrections. By setting up inverted welding of engine room sections, no additional scaffolding is needed, reducing costs. By setting up the flipping of engine room pre-assembly sections, the number of flipping and lifting / disassembling operations is reduced. By aligning the joints in the longitudinal direction, structural continuity and assembly accuracy are ensured.

The application provides a point cloud encoding method and device based on a prediction tree, equipment and a storage medium. The method comprises the following steps: obtaining a target point cloud, the target point cloud comprising N points; constructing a main prediction tree based on part of the main nodes in the N points; inserting the adjacent points of the main nodes in the remaining points into the main nodes to obtain a target prediction tree of the target point cloud for each main node in the main prediction tree; and encoding the target point cloud based on the target prediction tree. That is, the application takes the main nodes as the center, optimizes the connection relationship between the local points, and prevents the connection of points far away from each other. The target prediction tree obtained in this way realizes the optimal ordering of the local points, improves the construction accuracy of the target prediction tree. When prediction is performed based on the accurately constructed target prediction tree, the prediction accuracy of the target point cloud can be improved, and the encoding efficiency of the target point cloud is further improved.

The application discloses a kind of dam deformation prediction method, equipment, storage medium and product, the prediction method includes preprocessing to dam monitoring data;The environmental data after pretreatment is extracted to depth feature, and environment characteristic is obtained;The reservoir water level after pretreatment and environment characteristic are carried out cluster analysis, and according to the time domain division of time factor and dam survey point displacement according to cluster analysis result, obtain the cluster division result of different time periods;According to each cluster division result, respectively construct sample data set;Each sample data set is used to train and test Transformer-LSTM model respectively, and the dam deformation prediction model of each time period is obtained;Obtain the data to be predicted, and the dam deformation prediction model corresponding to the time period of the data to be predicted is used to predict the prediction data, and the dam deformation prediction result is obtained.The dam deformation prediction precision of the application is improved.

The present application discloses a device fault analysis method and related device, electronic equipment and storage medium, wherein the device fault analysis method comprises: obtaining target text about fault state of a target device; processing the target text based on a first large model to obtain a first fault analysis text, and processing the target text based on a second large model to obtain a second fault analysis text; wherein the first large model is obtained based on an initial large model through parameter fine-tuning, and the second large model is generated by retrieval enhancement; comparing a first confidence of the first fault analysis text with a second confidence of the second fault analysis text to obtain a first comparison result; and obtaining a target fault analysis text of the target device based on the first comparison result, the first fault analysis text and the second fault analysis text. The above scheme can improve the accuracy of the target fault analysis text while improving the robustness of the device fault analysis.

This application provides a method, apparatus, equipment, and medium for generating a secondary safety measures sheet for a technical upgrade substation. The method includes acquiring secondary equipment information and main wiring diagram information of the technical upgrade substation; performing correlation analysis on the secondary equipment information and main wiring diagram information of the technical upgrade substation based on preset substation information to determine the equipment correlation information corresponding to the technical upgrade of the substation; the preset substation circuit model includes preset secondary equipment information within the substation, preset main wiring diagram information, and preset correlation circuit information between each equipment bay; and generating a secondary safety measures sheet for the technical upgrade substation based on the equipment correlation information, thereby improving the accuracy of the secondary safety measures sheet generation.

This application discloses a method, storage medium, and program product for determining the semantics of a problem, relating to the field of artificial intelligence technology. The method includes: acquiring user questions that do not match within a preset time period to obtain a problem to be maintained, and acquiring a target standard question corresponding to the problem to be maintained; acquiring tags matching the problem to be maintained from a tag library to obtain a candidate tag set, and constructing a first prompt word based on a generation instruction, the problem to be maintained, and the candidate tag set. The generation instruction is used to mask a preset vocabulary according to the candidate tag set and generate at least two semantic expressions for the problem to be maintained; inputting the first prompt word into a target expression generation model to generate a candidate semantic expression set corresponding to the problem to be maintained; determining the target semantic expression from the candidate semantic expression set, and adding the target standard question and the target semantic expression to a problem matching library. This improves the efficiency and accuracy of determining the semantics of a problem and enhances the accuracy of the business service platform's responses.

The present application relates to artificial intelligence, and provides a drug candidate library construction method, device, equipment and storage medium. The method performs site mutation on the initial protein to obtain a new protein, performs graph characterization on the new protein and the initial protein to obtain a new characterization vector and an initial characterization vector, calculates a spatial structure loss value of the new protein and the initial protein, inputs the new characterization vector and the spatial structure loss value into a protein property prediction model to obtain a predicted property, and screens a target protein from a plurality of new proteins. Amino acid sequences are generated based on antigen-antibody complexes and disease antigens, and the target protein and the amino acid sequences are combined to improve the rationality of generating the drug candidate library. In addition, the present application also relates to blockchain technology, and the drug candidate library can be stored in the blockchain.

The disclosure provides a three-dimensional model construction method and device, electronic equipment and computer readable storage medium, relating to the technical field of artificial intelligence, and the method comprises: acquiring a two-dimensional image of a target object; determining a semantic segmentation feature and a semantic segmentation graph corresponding to the target object according to the two-dimensional image of the target object; determining a two-dimensional main stem feature corresponding to the two-dimensional image of the target object according to the two-dimensional image of the target object; performing feature fusion processing on the semantic segmentation graph, the semantic segmentation feature and the two-dimensional main stem feature corresponding to the target object to determine a fused two-dimensional feature of the two-dimensional image; acquiring a plurality of three-dimensional points in a three-dimensional space; determining the fused two-dimensional feature corresponding to the projection point of each three-dimensional point in the two-dimensional image of the target object based on the fused two-dimensional feature corresponding to the two-dimensional image; determining the spatial occupancy probability of each three-dimensional point in the three-dimensional model of the target object, so as to construct a three-dimensional model of the target object according to the spatial occupancy probability corresponding to each three-dimensional point.