53results about How to "Accurate association" patented technology

The invention relates to the technical field of remote sensing, and discloses an unfavorable geology detection method, system and device based on multi-source aerial remote sensing data fusion, and the method comprises the steps: obtaining laser radar data, hyperspectral image data, CCD image data, infrared image data and integrated navigation data of a target area, and carrying out the preprocessing; carrying out space matching processing on the preprocessed laser radar data, the preprocessed hyperspectral image data, the preprocessed CCD image data and the preprocessed infrared image data; fusing the laser radar data, the hyperspectral image data, the CCD image data and the infrared image data after application space matching processing for geological detection to obtain different geological detection data; and obtaining an unfavorable geological detection result of the target area in combination with different geological detection data. According to the method, the multi-source data fusion processing precision can be improved, multi-source heterogeneous information is effectively integrated, comprehensive and efficient detection of various unfavorable geologies is realized, the misjudgment and missed judgment risks are reduced, and the credibility of unfavorable geology detection results is improved.

The present invention discloses a supply chain material data management method and system, the method comprising receiving material data of upstream and downstream enterprises in the supply chain; performing named entity recognition for each material data, and analyzing the semantic dependency of attributes using dependency analysis technology; mapping different entities to corresponding concept nodes in an ontology, and establishing associations between entities and concepts; using a constructed material ontology, performing semantic standardized representation of entities, mapping entities to corresponding concept nodes in the ontology, and replacing them with standardized concept names or identifiers to form a standard material attribute feature library. The present invention realizes the collection and standardized processing of material data of upstream and downstream enterprises in the supply chain and the precise association of upstream and downstream material data.

The invention provides an identification and early warning method and system for dangerous behaviors of inland ships. The method comprises the following steps: acquiring infrared monitoring video image data of an inland river water area to obtain a standard data set; then, performing ship main shaft identification according to the standard data set, performing bow and stern identification according to a ship gray value, and performing ship motion direction judgment; then, according to a method based on sample generation, a large number of ship target tracking virtual samples are generated; then, inputting the generated ship target tracking virtual sample into a DVIS model tracking training framework to realize tracking training, and obtaining a tracking model; and finally, according to the obtained tracking model and input real sample data, analyzing motion track data and a motion mode of the ship, and carrying out identification and early warning on dangerous behaviors of the ship. According to the method, tracking of ship behaviors under the complex ship shore environment condition is achieved, early warning is conducted on the ship dangerous behaviors, and the recognition rate of the ship navigation dangerous behaviors is further increased.

The invention provides a method for accurately estimating target geometric features under laser radar point cloud integration. The method is divided into a modeling stage and an operation stage. In the modeling stage, a system state equation and a measurement equation are established according to the relation between the real geometrical characteristics and motion characteristics of a target during point cloud integration, the relation between the geometrical characteristics detected by a sensor and a sampling period and the relation between point cloud integration times. In the operation stage, firstly, original point cloud is preprocessed, a non-ground point cloud set is segmented, and then point cloud integration and clustering are performed to realize target detection, so that a target measurement set is obtained; secondly, carrying out one-step prediction, calculating target similarity, and carrying out target and trajectory association by utilizing the similarity; and finally, the optimal estimation of the geometric features and the motion features of the target is obtained by using Kalman filtering. According to the method, the precision of target geometric feature estimation under the point cloud integration method can be improved, the small target detection performance of the low-line-number laser radar is enhanced, and the cost of a target detection system based on the laser radar is reduced.

The invention relates to the technical field of life cycle traceability, in particular to a full life cycle traceability system and method based on intelligent washing. The method comprises the following steps: acquiring washing clothes and user information, generating an RFID identification code, binding the RFID identification code with the user information, creating a user-clothes binding relationship, performing digital mirror image copying on the binding relationship, generating a clothes data file in combination with a database chain technology, and predicting the service life of the clothes by analyzing clothes state data and predicting the service life of the clothes. And making a personalized washing plan. And executing the washing plan and monitoring the washing result, and finally updating the clothes data file according to the washing effect to generate a washing traceability file. According to the invention, safer and more accurate full-life-cycle traceability operation is realized.

The utility model relates to cell culture tool technical field especially, more particularly to an array formula multi -hole separation cell culture dish. The utility model provides an array formula multi -hole separation cell culture dish, solves the technical problem that cell culture dish in prior art can only culture same kind of cell under same environment. An array formula multi -hole separation cell culture dish, including frame, culture cavity, culture cavity set up in frame, and mark, mark set up in frame, and, every mark corresponds an independent culture cavity, array formula multi -hole separation cell culture dish sets up a plurality of independent culture cavities, and every culture cavity can be regarded as an independent'small culture dish'. This makes under same frame, to same kind of microorganism in different nutrient solution, medicine or other environmental conditions can carry out culture experiment simultaneously.

The invention discloses an intelligent warehouse management system and method based on high-precision indoor positioning, and relates to the technical field of warehouse positioning. A first corresponding relation among shelf number data, first quality data, goods quantity data and goods name data is established, and an inventory monitoring feedback mechanism is established; comparing the current goods quality data with the minimum goods quality data, establishing a warehouse management coordinate system, generating goods name data, shelf position coordinate data and a route map according to the warehouse management coordinate system, sending the data and the map to a corresponding warehouse personnel terminal, generating a plurality of secret key data according to a time period, and sending the secret key data to the warehouse personnel terminal; according to the method, the positions of the goods and the positions of the warehousing personnel are accurately associated in real time, so that the optimal goods taking path is automatically planned, the high efficiency, the accuracy and the safety of warehousing operation are realized, the warehousing, storage, inventory and ex-warehouse processes of the goods are optimized, the real-time performance and the accuracy of inventory monitoring are remarkably improved, and the working efficiency is improved. And strict control of access of the sensitive module is ensured.

The invention discloses a conductance cell system and method for double-range correction, and belongs to the technical field of analytical instruments, the system comprises a first conductance cell and a second conductance cell which are connected in series through a pipeline, and a processing unit connected with the first conductance cell and the second conductance cell. The first conductance cell is suitable for high-concentration detection, and the second conductance cell is suitable for low-concentration detection. The method comprises the following steps: firstly, establishing two calibration curves of different measurement ranges for two conductance cells, and determining critical points of the two curves; during detection, a sample sequentially flows through the two conductance cells, the processing unit selects one of the high-concentration calibration curve and the low-concentration calibration curve for data processing according to a comparison result of a real-time detection signal and a critical point, and finally a concentration value is output. According to the invention, through a series connection structure and intelligent curve selection, the detection range of a single conductance cell is effectively widened, the measurement precision in a full scale is remarkably improved, and automatic and high-precision detection in a wide concentration range is realized.

The invention discloses a method and system for verifying an RISC-V processor and a computer readable storage medium. The method comprises the following steps: analyzing an RISC-V official manual and a micro-architecture user manual, and generating a static instruction-resource mapping table; and generating a first test instruction sequence for each instruction in the static instruction-resource mapping table, executing the first test instruction sequence by using an RISC-V processor simulation model constructed by a software simulator, and dynamically calibrating the static instruction-resource mapping table in the execution process. And traversing the instruction and resource mapping relationship in the calibrated static instruction-resource mapping table, analyzing RISC-V processor verification logic, and if a conflict is found, outputting a conflict report so as to complete defect repair before RTL code writing. According to the application, hardware behaviors can be accurately associated, the problem of disjunction of semantics and micro-architecture is solved, and conflict prediction in an architecture design stage and end-to-end automatic verification from instruction semantics to micro-architecture behaviors are realized.

The application provides an information association method and device, electronic equipment and storage medium, relates to the technical field of communication, and solves the technical problem that in the related art, other users cannot guarantee the security of service data based on the terminal corresponding to a user accessing related services. The method comprises the following steps: receiving an information association request sent by a terminal; in the case that the secret card identifier of the first secret card is the same as the secret card identifier included in the opening information of the first account, and the first field included in the opening information of the first account is empty, sending a first verification code to the terminal, the first field being used to represent the terminal identifier corresponding to the account identifier of the first account; in the case that the first verification code sent by the terminal is received, determining the terminal identifier of the terminal as the terminal identifier corresponding to the account identifier of the first account, and determining the secret card identifier of the first secret card as the secret card identifier corresponding to the account identifier of the first account.

The invention discloses a semantic alignment enhanced lane line detection method based on a Mama framework. The method comprises the following steps: acquiring a lane line data set and inputting the lane line data set into a backbone network for multi-stage feature acquisition; flattening the feature map into a one-dimensional sequence by using a dynamic multi-scale adaptive screening module, stacking different levels of features, and highlighting lane line information through weights; then, through a Mama X branch, through global pooling and convolution, short-distance dependence is captured; then semantic completion is carried out on the output of the dynamic multi-scale adaptive screening module and the output of the Mama X branch through a semantic alignment fusion module, and alignment enhancement features are output; effective features are scanned through a gating module in the Mamba Z branch, and then the state is updated position by position through a scanning module to establish long-distance dependence; and inputting a feature sequence output by the Mama Z branch to a detection head, and outputting a lane line prediction map by continuously updating the position of a prior frame. According to the method, dynamic multi-scale adaptive screening, Mama architecture and semantic alignment fusion are combined, a long-distance dependency relationship can be established for the lane line, and the detection precision of the lane line is improved.

This invention discloses an integrated small embedding cassette and its tissue bottle for a pathological tissue embedding cassette sorting system, comprising a tissue bottle and an integrated small embedding cassette; the tissue bottle includes a top cover and a bottom cover, the inner wall of the top cover having a threaded structure, and the top and bottom covers being detachably connected via the threaded structure; the integrated small embedding cassette is horizontally positioned inside the tissue bottle, and the bottom cover has a sealed cavity for containing liquid; the integrated small embedding cassette includes a body and a lid, the body and lid being integrally formed. This invention, through integrated structural design, integrates the traditionally separate tissue bottle and the integrated small embedding cassette into a coaxial assembly structure, eliminating the sample transfer step, significantly reducing operational complexity, and minimizing reliance on manual labor. By setting a sealed threaded connection between the top and bottom covers, formaldehyde gas leakage from formalin solution is effectively reduced, improving biosafety.

The invention provides an automatic identification and tracking method and system for a lottery ticket bundle, and relates to the technical field of lottery ticket bundle identification and tracking. Multi-angle data of the lottery ticket bundle are acquired, three-dimensional contour data of a plastic package belt are synchronously acquired, and the two data are fused to generate a data set containing visual and spatial morphological characteristics; extracting the shape contour features of the edge area of the plastic packaging belt to reconstruct a three-dimensional edge path, and extracting the surface texture of the contact area of the plastic packaging belt and the lottery ticket bundle; judging the structural integrity of the plastic packaging tape according to the continuity and smoothness of the three-dimensional edge path, and evaluating the fitting tightness degree by combining the surface texture distribution uniformity of the contact area; the integrity and fitting degree result is compared with a reference model representing the standard state of the plastic packaging tape, the state of the lottery ticket bundle plastic packaging tape is marked, and finally lottery ticket bundle information with state marks and tracking codes are bound and written into a quality tracking database, so that precise recognition and information traceable management of the state of the lottery ticket bundle plastic packaging tape can be realized.

This invention proposes an intelligent remote emergency rescue management system capable of rapidly matching resources, relating to the field of remote emergency medical technology. The alarm receiving module triggers the case analysis module to generate priorities, the resource scheduling module allocates instructions to the drone control module, and after the drone completes deployment, the information matching module generates navigation information. Data from the person scanning the code is fed back to the system via the data association unit, forming a complete closed loop of resource scheduling-deployment-feedback. Through real-time data interaction between modules, the traditional emergency resource matching time is shortened from 10-20 minutes to within 2 minutes, while simultaneously improving the accuracy and utilization rate of drone AED deployment, achieving a qualitative leap in emergency response efficiency.

The invention discloses a method for predicting the association between lncRNA and disease based on a collaborative matrix decomposition of high-order perturbations and flexible ternary regularization, which belongs to the technical field of matrix decomposition and biological gene combination. The method comprises the following specific steps: obtaining the association matrix Z of lncRNA and disease; calculating the functional similarity matrix R of lncRNA based on the known association matrix Z; s and the semantic similarity matrix D of the disease s ; The multi-order correlation matrix calculated based on the known correlation matrix is ​​added to the known correlation matrix as a high-order perturbation; the global nonlinear structural similarity information of the similarity matrix is ​​obtained through similarity learning of flexible ternary regular terms; the objective function is optimized and iterated based on the collaborative matrix decomposition method to obtain the final prediction score matrix, so that the final prediction of lncRNA-disease association is more accurate.

The application discloses a double-link observable-based API interface data loss root cause positioning method, relates to the technical field of data operation and maintenance, and comprises the following steps: acquiring API requests from an API request query link and query request information of the API requests, wherein the query request information comprises first data identifiers and first time identifiers of to-be-queried data; acquiring data generation state information from a data generation link of a data production supply end, wherein the data generation state information comprises second data identifiers and second time identifiers corresponding to data generation tasks; establishing an association relationship between the API requests and the data generation tasks based on the first data identifiers, the first time identifiers, the second data identifiers and the second time identifiers; and if a response result of a target API request is data loss, determining a data loss root cause based on the association relationship, the target API request and a target data generation task. The application improves the positioning efficiency and accuracy of data loss faults.

The invention relates to the technical field of pavement disease detection, and discloses a pavement disease intelligent positioning and quantifying method, which comprises the following steps: acquiring road surface image data and navigation data corresponding to the road surface image data; based on the morphological information of the disease, quantifying the disease length, the disease area, the disease average width and the disease maximum width to obtain quantified disease characteristics; establishing a corresponding relation between the image and the acquisition sequence according to the quantized disease characteristics, and searching navigation data corresponding to the skeleton pixel points; calculating latitude and longitude coordinates of scanning line boundary points according to latitude and longitude coordinates of a scanning center point in the navigation data, and converting any skeleton pixel point in the image into geographic coordinates of a disease so as to realize positioning of a disease target in a real geographic space; and making a disease GIS map based on the geographic coordinates of the diseases and the quantitative disease characteristics. According to the invention, each pixel point in the image is regarded as an independent positioning unit, so that the morphology of the disease can be presented more accurately.

The invention provides a mobile phone end face action voice recovery system based on convolution and an attention mechanism, and relates to the technical field of voice processing, and the system comprises a data acquisition module, a data processing module, a model training module and a voice generation module. The data acquisition module calls a mobile phone acceleration sensor to synchronously acquire facial acceleration and voice data in real time and transmit the facial acceleration and voice data to the computer; the data processing module is used for receiving, aligning and storing data at a computer end and de-noising the data to enhance the signal-to-noise ratio; the model training module constructs a model, the acceleration data is converted into a Mel language spectrogram through a convolutional neural network attention model, and then voice is generated through a vocoder; and the voice generation module inputs the processed facial acceleration data into the trained model, generates voice and transmits the voice as required. The system effectively solves the existing problems, realizes the recovery from the facial action to the voice, and has a good application prospect.

The present application belongs to the technical field of chemical safety monitoring, and particularly relates to a chemical gas leakage detection method based on multi-information fusion, which is used for a mobile inspection platform, the mobile inspection platform is equipped with an image acquisition device, multi-type gas concentration sensors and a GPS / IMU combined positioning module, and the method comprises the following steps: S1: multi-source data synchronous acquisition and preprocessing, real-time video stream data of a chemical scene is acquired through the image acquisition device of the mobile inspection platform, gas concentration data of corresponding spatial positions are acquired through the multi-type gas concentration sensors, and timestamp alignment and standardization preprocessing are performed on the two types of data. The present application can realize early prediction, accurate positioning and hierarchical emergency disposal of chemical gas leakage through the following steps: spatio-temporal synchronous multi-source data acquisition, three-dimensional semantic mapping, rule-based high-level semantic reasoning, multi-modal fusion and double verification.

This invention proposes a multimodal driven and dynamically optimized method and system for power plant inspection image segmentation, belonging to the field of computer vision technology. The method includes: acquiring inspection sample images; generating initial pseudo-labels using a pre-trained visual language model and a multimodal large language model; inputting the inspection sample images into the visual model to obtain dense features, aligning them cross-modally with text semantic embeddings to obtain enhanced visual features; constructing a transition matrix based on image features and enhanced visual features, and inputting these features into a decoder to obtain a dual-path prediction mask, which is then fused to generate a segmentation probability map; optimizing the initial pseudo-labels based on the segmentation probability map and the transition matrix, and using the optimized pseudo-labels to construct a supervision signal to guide the generation of the transition matrix; iteratively optimizing until convergence to obtain a trained image segmentation network, which is then used as input to the inspection image to be segmented to obtain the segmentation result. This improves the segmentation accuracy and generalization ability of inspection images.

The present invention relates to a method and system for associating multiple vehicles in a cross-domain roadside perception, the method comprising the following steps: constructing a network graph structure for each roadside sensor node in a region, for integrating sensor perception data and calculating the corresponding node traffic status; constructing a spatiotemporal transfer model of traffic status based on a dynamic graph, and calculating the spatiotemporal correlation similarity between trajectory pairs under each node based on the model; extracting vehicle appearance features, fusing them with the spatiotemporal correlation similarity of trajectories to obtain an enhanced similarity index, and calculating the normalized enhanced similarity index using a spatiotemporal feature mask; constructing a similarity matrix for vehicle perception trajectory data sets of different nodes, and realizing the corresponding vehicle target association based on the similarity matrix. Compared with the prior art, the present invention is oriented to a roadside sensor network at the scale of an urban road network, and can effectively realize the rapid and accurate association of roadside perception data by comprehensively utilizing vehicle appearance features and the spatiotemporal transfer characteristics of traffic status between sensor nodes.

This utility model discloses an automatic scanning and data recording device for an infrared emissivity tester, relating to the field of infrared detection equipment technology. It includes a worktable, a support rod, an infrared emissivity testing lens, an infrared emissivity testing main control unit, a computer main control unit, and a moving platform. One end of the support rod is vertically mounted on the worktable, and the infrared emissivity testing lens is mounted on the other end of the support rod. The infrared emissivity testing lens is electrically connected to the infrared emissivity testing main control unit, which is electrically connected to the computer main control unit. The moving platform is mounted on the worktable and is used to move the sample horizontally. This invention overcomes the shortcomings of existing infrared emissivity testers, which require manual sample movement, resulting in low efficiency and large errors.

This invention discloses a furnace temperature control method, relating to the field of intelligent control of electronic packaging welding processes. The method includes: collecting real-time temperature data and welding process parameters of the substrate to be welded, and acquiring post-weld deformation data; aligning and fusing the real-time temperature data, process parameters, and deformation data to extract key features of the furnace temperature curve, and constructing a data record set by associating them with the deformation of corresponding measuring points; based on the data record set, establishing a quantitative prediction model using regression analysis or machine learning algorithms; under preset process constraints, optimizing the furnace temperature curve setpoint with the predicted warpage as the optimization objective, calculating the corresponding predicted warpage using the quantitative prediction model, generating the optimal furnace temperature curve setpoint, and sending it to the welding equipment for execution. By constructing a quantitative prediction model using temperature data from sensitive points and post-weld deformation, the optimal furnace temperature curve is generated through reverse optimization to suppress welding warpage.

Embodiments of the invention relate to an audio adjustment method and apparatus, a display device and a storage medium. The method comprises the steps of obtaining a position parameter of a target object in a preset area in front of a screen of the display device; determining an offset state of the target object according to the position parameter; determining an adjustment strategy of audio equipment of the display equipment according to the position parameter and the offset state; and adjusting an audio parameter and / or an audio equipment angle of the audio equipment according to the adjustment strategy. Therefore, the audio equipment of the display equipment can be adjusted according to the position parameter and the offset state of the target object in front of the screen of the display equipment, so that the audio can be accurately associated with the position of the target object, and a relatively good audio and picture tracking effect can be achieved at any watching position of a user; the problem that in the prior art, the sound and picture tracking effect becomes poor due to the fact that the watching position of a user deviates from the middle is solved.

This invention provides an AI text-based order placement method and system based on multimodal parsing and context awareness, belonging to the field of artificial intelligence technology. The method includes acquiring multi-source heterogeneous order data; preprocessing the multi-source heterogeneous order data to generate standardized text data; dynamically slicing the standardized text data exceeding a preset length threshold using an intelligent slicing engine to generate a semantically continuous text slice sequence; inputting the text slice sequence into a cascaded routing hub for hierarchical parsing to obtain parsing results; based on the parsing results, performing parallel product retrieval using a hybrid strategy recall engine; processing the product retrieval results to obtain a candidate product set; and performing context-aware completion processing on the candidate product set, completing missing product attributes based on the user's historical order knowledge graph and resolving fuzzy referencing to generate a standard order object. This achieves automatic, highly accurate, and low-cost parsing and input of order text.

The application discloses a multi-source heterogeneous data correlation retrieval method and system based on a unified identifier, a terminal and a medium, and relates to the technical field of information retrieval.The technical solution points are as follows: the application uses a unique identifier to perform strong correlation mapping between all scattered and heterogeneous physical storage and logical indexes at a logical level, and constructs a unified data view centered on an entity, so that data originally stored in object files, metadata tables, structured records, relationship graphs and retrieval indexes can be stably and accurately correlated and traced.Especially, the two-stage retrieval mode of keyword preliminary screening and graph expansion first efficiently locates a target through a retrieval engine, and then uses graph mining to find the correlation network.The application effectively solves the disadvantage that the existing retrieval scheme cannot perform correlation resource expansion, upgrades data query from single finding to network discovery, and improves the data correlation discovery rate and query completeness in a complex business scenario.

The invention discloses a multi-source attack detection method for computing power cluster security protection, and belongs to the technical field of host security attack detection. The method comprises the following steps: inputting an operating system auditing log of a computing node in a computing power cluster to be identified into a pre-trained time sequence anomaly detection model to calculate an anomaly probability score of the operating system auditing log, when the anomaly probability score exceeds a threshold value, judging that the operating system auditing log is attacked, and otherwise, judging that the operating system auditing log is safe; the pre-trained time sequence anomaly detection model is obtained through the following steps: collecting an operating system audit log of each computing node, analyzing an event in the log into a standardized quintuple event, and obtaining a global cause and effect graph based on the event; active entity nodes in the global causal graph are screened, and multi-dimensional feature coding is carried out to generate a feature sequence; and inputting the feature sequence into a pre-constructed time sequence anomaly detection model to obtain a trained time sequence anomaly detection model. According to the invention, the problem that the existing detection technology is difficult to restore a cross-host complete attack link is solved.

The film and television script extraction method and device, the storage medium and the computer device provided by the application, after the audio and video file of the film and television is split into a video file and an audio file, the video file is subjected to feature recognition to obtain a subtitle text, a speaker face information and a video understanding text; and the audio file is subjected to speech understanding to obtain a speech transcription text and a speech understanding text; wherein the speech transcription text can be corrected into a standard transcription text with higher accuracy through the subtitle text. Therefore, based on the speaker face information, the standard transcription text and the dialogue segment of each speaker in the audio and video file are aligned, the speaker information with accurate segmentation and coherent semantics can be obtained, then the script information is constructed by combining the character profile text generated by the profile analysis of the speaker based on the video, the speech understanding text and the speaker information, the script information can cover the related feature description of the character on the basis of the dialogue content, thereby enriching the content and depth of the script.

The invention discloses a method for separating elastic deformation and pore elastic deformation and related equipment, and relates to the field of geodesy, and the method comprises the steps: taking a preset number of InSAR earth surface deformation time sequences as an initial mass center, and employing a spatial clustering algorithm to obtain a plurality of clusters; for each cluster, determining the category of the cluster based on the average value and spatial distribution characteristics of the InSAR earth surface deformation time sequence in the cluster; if the category of the cluster is the pore elastic deformation dominant category, obtaining a pore elastic deformation dominant deformation time sequence according to the InSAR earth surface deformation time sequence in the cluster; if the category of the cluster is a seasonal pore elastic deformation and elastic load deformation aliasing category, performing principal component analysis on the InSAR earth surface deformation time sequence in the cluster to obtain an elastic load deformation sequence and a seasonal pore elastic deformation sequence; according to external data, separation is proved to be successful. According to the method, the elastic deformation and the hole elastic deformation can be effectively separated from the InSAR earth surface deformation.

The invention relates to an optical mark positioning device for PC component mold visual inspection and a detection method. The method comprises the following detection steps: step 1, a preparation stage: selecting a base matched with the height of a to-be-detected mold, assembling the optical mark positioning device, and loading component quality inspection data by a machine vision system background; secondly, a mold and a mark are placed, specifically, an operator places the PC component mold on a mold table, and then an optical mark positioning device is adsorbed to the mold table according to a preset rule; step 3, triggering detection: triggering a machine vision system; step 4, image acquisition and processing: shooting by a camera, and identifying an optical mark and identification information thereof in an image by software; the machine vision system calculates the actual position and posture of the mold according to the marked position, the actual position and posture are compared with standard data, and whether the mold is qualified or not is judged; and step 6, result feedback and mark removal: the HMI displays the result, and the magnetically attracted mark positioning device is taken down from the mold table for storage after the detection is completed.