202 results about "Defect repair" patented technology

The invention discloses a defect repair method based on digital twinning and friction stir welding technologies, and relates to the technical field of intelligent manufacturing and digital twinning, and the defect repair method comprises the following steps: synchronously capturing full-dimensional data of a welding area through a multi-mode sensor array integrated by an actuator; secondly, segmenting defect boundaries by adopting a deep learning algorithm, constructing a dynamic twin model in combination with thermal-force field coupling simulation, and accurately mapping defect three-dimensional features; generating a repair track according to the twinborn model, converting the repair track into a robot joint instruction through a curved surface parameterization mapping algorithm, and implanting real-time anti-collision constraint; in the repairing process, based on reinforcement learning control of the material rheological resistance and the temperature gradient, the rotating speed, the advancing speed and the down force of the tool are dynamically adjusted; and after repairing, micro-focus CT scanning is started immediately, actually measured data is compared with twinborn prediction, and when the deviation exceeds a threshold value, a re-repairing process is triggered automatically. The method solves the problems that a traditional method depends on manual intervention and the precision of a sensor is easily interfered by the environment.

The embodiment of the invention discloses a circuit board defect automatic detection method and system based on machine vision, which are used for improving the precision and efficiency of circuit board defect detection and repair, and the method comprises the following steps: obtaining a surface image data set of a target circuit board; performing image preprocessing operation on the surface image data set to generate a preprocessed image data set; inputting the preprocessed image data set into a pre-trained defect feature extraction model, and performing multi-level feature fusion processing on each piece of image data through the defect feature extraction model to generate a multi-dimensional defect feature set; determining a defect positioning information set of the target circuit board according to a matching degree calculation result between the multi-dimensional defect feature set and a preset defect feature template; and transmitting the defect positioning information set to a defect repair control terminal, and triggering the defect repair control terminal to generate a repair path planning instruction according to the defect positioning information set.

The invention discloses an RFID tag production line defect real-time detection system and compensation method based on machine vision, and belongs to the technical field of intelligent manufacturing and quality control. The system comprises an image acquisition module, a defect detection module, a compensation execution module and a feedback control module, based on defect types and positions, a grading compensation strategy is triggered, the grading compensation strategy comprises real-time printing parameter adjustment, laser accurate repair of a defect area or automatic rejection of a mechanical arm, and a process parameter library is synchronously updated through an industrial Internet of Things platform. The innovation points are as follows: (1) a multi-modal defect data fusion method is provided, and the detection robustness under complex working conditions is improved; (2) a lightweight double-branch detection network is designed, and the detection speed and precision are both considered; and (3) developing a compensation instruction cooperative control algorithm to realize seamless connection between defect repair and production line rhythm. According to the scheme, the defect omission ratio can be reduced to 0.5% or below, the compensation response time is shortened to be within 200 ms, and the production line yield and the production efficiency are remarkably improved.

The invention provides a software code defect detection method and system based on program code feature fusion, and the method comprises the steps: carrying out the grammar and structure inspection of a code through a static analysis tool, and extracting defect features related to control flow chaos, exception handling and resource leakage; running a preset test case through a dynamic analysis tool, capturing an execution path and an abnormal behavior in a runtime state, and obtaining defect features which are not covered by static analysis; if the output result of the decision tree model is that defects exist, grouping comprehensive defect feature vectors by adopting a density-based clustering algorithm, determining the types and distribution ranges of the defects, and selecting the density clustering algorithm to process defect features in non-spherical distribution; and according to a clustering result, generating a defect repairing suggestion, combining code logic and execution path information, and determining a specific position and an influence range of the defect. According to the method, the stealth defect in the code can be effectively identified and positioned, the software quality and reliability are improved, and timely and accurate defect repairing guidance is provided for developers.

The invention provides a cranio-maxillofacial hard tissue deletion repair method based on a general repair model, and relates to the technical field of jaw defect reconstruction, the method comprises the following steps: constructing a cranio-maxillofacial hard tissue general repair model by using a plug-and-play conditional attention mechanism and a query generator based on curvature perception; inputting the cranio-maxillofacial hard tissue point cloud data into a cranio-maxillofacial hard tissue general repair model, and training by using a weighted loss function to obtain a trained cranio-maxillofacial hard tissue general repair model; performing de-noising processing on the missing repair point cloud features to obtain de-noised missing repair point cloud features; and carrying out point cloud gridding modeling processing by using the denoised deletion repair point cloud features to obtain a cranio-maxillofacial hard tissue deletion repair result, and completing the deletion repair of the cranio-maxillofacial hard tissue. The problem that repair and reconstruction of hard tissues at the head part are difficult to solve uniformly is solved.

The invention relates to the technical field of defect repair, and discloses a fabric texture defect repair method and device based on a generative adversarial network. The method comprises the following steps: decomposing a defect fabric image to be repaired to obtain a fabric texture direction feature matrix and a defect area positioning mask; performing cross-domain feature unified processing on the fabric texture direction feature matrix to obtain a unified feature code; performing similarity retrieval to obtain an optimal matching texture reference feature; inputting the defect area positioning mask and the defect fabric image into a first-stage coarse repair generator for structural reconstruction to obtain an initial fabric repair image; and inputting the initial fabric repair image into a second-stage fine repair generator for wavelet multi-scale detail optimization and boundary fusion correction to obtain a target fabric repair image. According to the method, visual mutation of the repaired area and the original area is effectively eliminated, the natural transition effect of seamless connection is achieved, and the calculation efficiency is optimized while the repair quality is guaranteed.

The invention provides a defect repairing method and device based on a large model, electronic equipment and a medium, and relates to the field of defect repairing, and the method comprises the following steps: obtaining original log data generated in real time; analyzing the original log data through a preset model, and determining defect logs and user operation parameters; determining a target code file corresponding to the defect log; repairing the target code file through a preset model, and generating a repairing scheme to determine a repaired code file; and submitting the repair code file to a code warehouse to cover the target code file, determining an updated code warehouse, and determining a production system instance according to the updated code warehouse. According to the method, the original log of the deployed system is obtained in real time, the defect log and the associated user operation parameters are automatically analyzed and determined, the target code file is positioned, the repair scheme adjustment code is generated, then the repair code is submitted to the warehouse for updating, the production system instance is determined, and automation of the whole process of defect repair is achieved.

The invention discloses a paper product packaging defect real-time detection system based on edge calculation, and relates to the technical field of packaging defect detection. Comprising a multi-modal data acquisition module for acquiring packaging multi-dimensional image data by using a camera and a sensor; the edge intelligent processing unit and the heterogeneous architecture are combined with dynamic scheduling to realize rapid data processing; the defect feature enhancement network is used for improving an algorithm to accurately extract defect features; the edge decision optimization engine is used for reinforcing learning to optimize a detection strategy; the industrial-grade communication module is used for guaranteeing data transmission through 5G and TSN hybrid; the closed-loop repair execution system is used for realizing automatic repair of defects; in addition, auxiliary modules such as a traceability module and an energy optimization module are further arranged, and all the modules cooperate to achieve efficient detection and repair of packaging defects. The paper product packaging detection level is greatly improved, the speed is improved by 2.5 times, energy consumption is reduced, detection and closed loop repairing are achieved, intelligent upgrading of a production line is promoted, and the labor cost and the product reject ratio are reduced.

The invention relates to the technical field of friction stir repair, and discloses a multi-dimensional defect friction stir solid-phase repair planning system and a defect repair method. The system comprises a defect acquisition unit for acquiring multi-dimensional defect data of a workpiece and generating a time-space correlation data set covering defect depth distribution, a material heat affected zone range, a friction tool wear state and environment temperature and humidity parameters; the feature reconstruction unit decomposes the data set and separates core and abnormal feature tensors; the repair planning unit generates a multi-region cooperation scheme containing a tool path, a pressure sequence and a rotating speed strategy in combination with the core features and the process constraints; the dynamic adjusting and optimizing unit monitors abnormal characteristics and adjusts the scheme when conditions are met; the collaborative strategy unit responds to cross-regional defect linkage abnormity, allocates a standby tool and updates a track offset; and the feature fusion unit fuses the multi-scale monitoring features to generate a repair quality evaluation feature set. The system enhances the comprehensiveness and adaptability of complex defect repair.

The invention discloses an AI software system defect repairing method, device and equipment of a government affair platform and a medium, and relates to the technical field of computers, and the method comprises the steps that target data of a current platform AI software system in the running process is obtained through an eBPF probe loaded by a K8s cluster of the government affair platform, and defect fingerprints are determined based on the target data; determining a target defect classifier based on the graph neural network, the teacher model, the student model, a preset distillation mechanism and a KL divergence loss function, determining a target strategy composer by using reinforcement learning and a preset strategy library, and determining a target defect repair strategy based on the defect fingerprint, the target defect classifier, the business data and the target strategy composer; and performing defect repair on the current platform AI software system by using the target defect repair strategy, verifying the repaired AI software system, and if the verification is passed, completing the defect repair operation. And the AI system defect automatic detection and repair efficiency is improved.

The invention belongs to the technical field of display panel repairing, and discloses a display panel laser repairing method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining a panel image of an OLED display panel, and carrying out the defect detection of the panel image, obtaining defect positions, defect sizes, defect types and repair formulas of all defects capable of being repaired by laser in the OLED display panel, and performing repair path planning according to a coordinate sequence repair mode, a same formula sequence repair mode and a comprehensive repair mode according to the defect positions, the defect sizes, the defect types and the repair formulas. And obtaining an optimal repair path with the minimum defect repair time, and performing laser repair on the defect capable of being subjected to laser repair in the OLED display panel based on the optimal repair path. The OLED display panel is subjected to laser repair by comprehensively considering the optimal repair path planned by multiple repair sequences and time cost, so that the laser repair efficiency of the display panel is improved.

According to the mask defect in-situ repairing method, the femtosecond laser is adopted for defect repairing, and all the advantages of the femtosecond laser are absorbed. Femtosecond laser is ultrashort pulse laser with'femtosecond 'as a time unit, the pulse duration time of the femtosecond laser is extremely short (femtosecond magnitude), and the peak power of the femtosecond laser is extremely high (the maximum can reach pat watt). Therefore, according to the repairing method, the repairing precision can be reduced to 15 nm, the heat affected zone is smaller than 1 micron, the repairing time can be shortened to 100 ms for the defect of 100 nm, the roughness of the repaired surface is smaller than or equal to 0.5 nm, meanwhile, the good effects of high repairing precision, low heat affected zone, high repairing speed, low equipment cost and simple operation are achieved, and the rejection rate of the mask is reduced. The method is especially suitable for repairing advanced process masks, such as EUV and ArF, and display panel masks, such as OLED and FMM, and MEMS device masks.

This invention provides a comprehensive digital and intelligent operation and maintenance management method and system for power distribution networks, relating to the field of computer data processing technology. The method includes: S1, obtaining pole and tower information collected by drones during line inspections, performing defect mining and analysis on the pole and tower information, and integrating the analyzed defect information with the pole and tower information to form a pole and tower information collection table; S2, selecting and extracting corresponding data from the pole and tower information collection table, and visualizing the data on a GIS map containing the lines obtained from the pole and tower information collection table using preset markers to generate an inspection status map; S3, statistically classifying the analyzed defect information and matching it through a big data platform to generate a defect repair and management summary table; S4, analyzing the faults using an AI model and a big data platform, combining the inspection status map and the defect repair and management summary table, obtaining priority-ranked repair tasks, and proposing corresponding solutions.

The invention discloses a program defect repairing method and device, equipment and a storage medium. The method comprises the steps that a defect code segment is obtained from a first program code which is reported to be wrong, and a similar defect code segment and a similar repair patch corresponding to the defect code segment are inquired in a historical code library; constructing a first prompt word based on the defect code segment, the similar defect code segment and the similar repair patch, generating a repair patch based on the first prompt word, and repairing the first program code through the repair patch to obtain a second program code; and under the condition that the verification of the second program code is not passed, regenerating a repair patch based on a defect code segment appearing in the verification process of the second program code, and repairing the second program code through the newly generated repair patch. According to the method, the big language model is guided to generate the high-credibility repair patch through the historical similar defects and the repair patch thereof, and the problem that in the prior art, the repair patch is unreliable due to the fact that the big language model is separated from an actual repair case is solved.

The invention relates to the technical field of artificial intelligence, and discloses an application software code defect automatic detection method and system based on artificial intelligence, and the method comprises the steps: obtaining a source code of to-be-detected application software, and carrying out the deep structure semantic coding of the source code, and obtaining a code semantic feature vector; performing context weight distribution on the code semantic feature vector to obtain weighted context aggregation representation; performing defect feature collaborative analysis on the weighted context aggregation representation to obtain defect types and position information; performing semantic association traversal on the defect type based on a preset defect knowledge graph to obtain an association repair information group; performing logic priority arrangement on the repair strategies in the associated repair information group to obtain a defect repair suggestion sequence; generating a code defect detection report according to the defect type, the position information and the defect repair suggestion sequence; the code defect detection efficiency can be improved.

The invention relates to the field of building detection, and discloses a defect repairing method, device and equipment for a building outer wall, and the method comprises the steps: building an outer wall surface image set of a target building; identifying defect type, size and depth information of each defect in the outer wall surface image; establishing a target three-dimensional model of the target building, and generating a position coordinate corresponding to each defect; and generating a repair path of each defect according to the type, the size, the depth and the position coordinates of the defect. The building outer wall defect detection efficiency and accuracy can be effectively improved, a detailed report of the defects can be automatically generated, analysis and future defect development state prediction can be performed according to the actual situation and historical data of the building, reasonable maintenance suggestions are provided, the safety of the building outer wall is ensured, and the method is suitable for popularization and application. And long-term maintenance of the outer wall is facilitated.

The invention discloses a welding seam defect detecting and repairing method which comprises the following steps: performing defect detection on a welding seam structure based on a plurality of defect detection modes to obtain a defect detection result; performing classification identification processing on the defect detection result to obtain corresponding defect information; and generating a corresponding repair strategy according to the defect information, and performing defect repair treatment on the weld joint structure based on the repair strategy. In the aspect of detection, detection and classification identification are carried out through multiple defect detection modes, so that weld defects are captured more comprehensively and accurately, omission and misjudgment are reduced, and the detection accuracy of a complex weld structure is improved; in the aspect of repairing, a targeted repairing strategy is generated based on accurate defect information, the quality problem caused by blind operation in traditional repairing can be effectively solved, the repairing failure risk is reduced, it is ensured that the quality of a repaired welding seam is more reliable, and the requirements of nuclear power equipment for the safety and reliability of the welding seam are met; therefore, the welding seam detection precision and the repair quality are remarkably improved.

The invention relates to an epitaxial growth temperature detection method, which comprises the following steps: providing a test wafer which comprises a calibration wafer and a temperature measurement wafer; performing defect treatment on the calibration wafer and the temperature measurement wafer so as to introduce crystal defects into the calibration wafer and the temperature measurement wafer; performing defect repair treatment on the calibration wafer at different target calibration temperatures, and obtaining defect repair information at corresponding temperatures; according to the target calibration temperature and the corresponding defect repair information, establishing a temperature measurement database used for representing the corresponding relation between the crystal state and the growth temperature; transferring the temperature measurement wafer into epitaxial equipment, and raising the temperature of the epitaxial equipment to an epitaxial temperature; obtaining crystal state information of the temperature measurement wafer at different positions; and obtaining the growth temperature corresponding to each crystal state based on the temperature measurement database and the crystal state information of the temperature measurement wafer. According to the epitaxial growth temperature detection method, temperature distribution in the epitaxial process can be effectively monitored and optimized, and the quality of a silicon carbide epitaxial film and the performance stability of a device are remarkably improved.

The invention discloses a multi-modal alignment and weak supervised learning-based pipeline defect detection and report generation method, which comprises the following steps of: performing data cleaning and standardization processing on pictures in a pre-acquired pipeline defect report and corresponding text information, and labeling the processed pictures, converting the processed picture and text information into high-dimensional semantic vector representation to obtain a text vector and a picture vector, and establishing a data set in combination with the annotation of the picture; based on the data set, training a multi-modal vector aligned large language model, and realizing defect detection and report generation to obtain a defect detection result and a report; performing validity verification and expert feedback correction on the defect detection result and report; the pipeline defect detection and report generation task can be efficiently and accurately completed, and the testing efficiency and the intelligent level in the defect repairing process are improved.

The invention discloses a software code defect automatic detection and repair system based on deep learning, and relates to the technical field of deep learning technology.A data acquisition module acquires multiple source codes and metadata and adapts to a mainstream programming language; the preprocessing module cleans codes, extracts features and divides data sets; the detection model is used for identifying 12 types of defects by using a Bi-LSTM (Bidirectional Long Short Term Memory) and Transform mixed architecture; the repair model generates a repair scheme based on CodeBERT; defect verification is integrated with static / dynamic verification; the system management realizes configuration, user, task and log management, and supports RBAC authority control. According to the method, the code defect detection accuracy and repair efficiency are improved, and multiple defect types and programming languages are covered; the repairing scheme adapts to the scene and is explained, so that the labor cost is reduced; model dynamic updating and cross-language adaptation are supported, a development process can be integrated, and the comprehensive effects of code quality improvement, efficiency improvement and maintenance cost reduction are achieved.

The invention belongs to the technical field of automobile die-casting dies, and discloses an automobile part die-casting die surface high-wear-resistance and corrosion-resistance treatment process which comprises the steps that a die is cleaned; polishing the surface; mold defects are recognized, and corresponding repairing measures are taken according to different defects; carrying out nitriding treatment on the cleaned and polished die subjected to defect repair; the mold is subjected to gas nitriding treatment, and then key parts and components are subjected to ion nitriding treatment; hard chromium plating treatment; chemical hole sealing and organic coating hole sealing treatment: multi-point detection is carried out, and it is ensured that the hardness of the nitriding layer and the hardness of the chromium plating layer meet the requirement. According to the method, fine defects of the mold can be found, and the wear resistance and corrosion resistance are improved through combination of gas nitriding treatment and key part ion nitriding treatment; through hard chromium plating treatment, surface performance strengthening, double hole sealing treatment, protection effect strengthening and adoption of the nano-powder addition amount and a pulsed electric field directional arrangement method, a plating layer is more uniform and compact, and the hardness and wear resistance of the plating layer are improved.

The utility model discloses a glass defect detecting and repairing all-in-one machine which comprises a machine table, the conveying mechanism is arranged on the machine table, and the conveying mechanism is used for conveying glass; the detection mechanism is arranged on one side of the conveying mechanism and is used for detecting the defects of the glass conveyed by the conveying mechanism; the first laser repairing mechanism and the second laser repairing mechanism are arranged on the machine table and located beside the conveying mechanism, and the first laser repairing mechanism and the second laser repairing mechanism are used for repairing defects on the glass conveyed by the conveying mechanism respectively. And the defect repair size range of the first laser repair mechanism is larger than that of the second laser repair mechanism.

The invention relates to the technical field of defect repairing, in particular to a defect repairing method, device and equipment for hot end components of a gas turbine, a storage medium and a product. Carrying out synchronous registration on the surface image and the temperature field distribution data; inputting the surface image and the temperature field distribution data after synchronous registration into a trained defect detection model for defect detection to obtain the defect type of each hot end component; and performing defect repair on each hot end component according to a defect repair strategy corresponding to the defect type, and identifying possible defects in the hot end component through a surface image of the hot end component and temperature field distribution data in multiple dimensions so as to determine a specific damage type in the hot end component. And corresponding defect repair strategies are selected based on different types of defects to perform defect repair on each hot end component, so that the defect repair effect is improved in a targeted manner.

The invention provides a pulse welding method for an irregular automobile part product, which comprises the following steps of: acquiring point cloud data on the surface of the product through laser scanning, dividing regular and irregular areas by adopting a point cloud segmentation algorithm, extracting geometrical characteristics, and respectively generating welding paths with path continuity and self-adaptability for different areas, welding parameters are dynamically adjusted in combination with a genetic algorithm; in the welding process, real-time data collection and a convolutional neural network are adopted to identify defects, and a repair path is generated through a reinforcement learning algorithm to execute laser repair and secondary welding; and finally, evaluating the welding quality by adopting a three-dimensional reconstruction technology. According to the method, the problems of path planning, parameter optimization, defect repair and the like in irregular product surface welding can be effectively solved, and the welding quality and efficiency are remarkably improved.

The invention discloses a two-dimensional code recognition and defect repair method and device, and the method achieves the effective integration of visible light, infrared and ultraviolet image features through the collection and preprocessing of a multi-modal image, greatly improves the feature recognition degree of a two-dimensional code under a complex background, and solves a problem that a conventional method is poor in adaptability to the complex background. According to the lightweight convolutional neural network defect detection model, pixel-level defect segmentation and multi-dimensional classification are realized, a defect severity grading mechanism is combined, an accurate basis is provided for intelligent defect evaluation, and the defect of lack of intelligent evaluation in the prior art is made up; for self-adaptive repair strategies of defects of different types and levels, the advantages of multiple algorithms such as texture synthesis, error correction coding and geometric correction are fused, and the repair precision of the two-dimensional code is greatly improved; a closed-loop verification mechanism of repair and recognition realizes linkage optimization of a repair process and a recognition result by dynamically adjusting repair parameters, and the problem of low efficiency caused by separation of repair and recognition is effectively solved.

The application discloses a multi-position defect repairing method based on repairing sequence scheduling and multi-agent cooperation. First, the defect analysis agent is used to identify the code error root cause and generate a defect analysis report. Then, the report, error code, local context, failed test cases and test error information are combined to build a repair context. Then, the multi-agent architecture is used to iteratively generate patches: the coordinator agent analyzes the dependency relationship between code blocks and schedules the repair sequence, the proposer agent generates a local candidate patch, and the coordinator evaluates and selects the optimal patch. Repeat the process until all repairs are completed and a complete patch is assembled. Finally, according to the compilation error and test failure report, the patch is executed in two stages of syntax and semantics refinement. The application overcomes the defects of the existing large model repairing method, such as lack of sequence scheduling and difficulty in handling code block dependencies, and realizes efficient repair of complex multi-position defects.

The invention discloses a defect repairing device and method for a metal component, and the device comprises a closed container which comprises a cabin body, a cabin door, an insulating cylinder, and an insulating storage platform; the bin door and the bin body are opened and closed to form a sealed cavity; the insulating cylinder is arranged in the sealing cavity, and an opening in one side faces the bin door; the insulating object placing table is arranged in the insulating cylinder and is used for placing a metal component; the gas pressurization system is located outside the closed container, communicates with the sealing cavity and is used for providing pressurized gas, so that the interior of the sealing cavity is pressurized to preset process pressure; the pulse current system comprises a pulse power supply and a current applying part, the pulse power supply is located outside the closed container, the current applying part is located in the insulating cylinder, the pulse power supply is conductively connected with the current applying part through a wire, and the current applying part is used for making contact with the metal component and applying pulse current. The application of the electric pulse treatment technology in defect repair of the metal component is realized, and the metallurgical-grade repair of the defects of the metal component is efficiently, quickly and accurately realized.

The present application relates to the technical field of patching material mix ratio determination, and particularly relates to an underwater patching material mix ratio determination method. A plurality of initial underwater patching material mix ratios are obtained; initial compressive strength, initial splitting tensile strength and initial fluidity corresponding to each initial underwater patching material mix ratio are determined; a multi-objective fitness function is constructed based on the initial compressive strength, the initial splitting tensile strength and the initial fluidity corresponding to each initial underwater patching material mix ratio; and each initial underwater patching material mix ratio is optimized based on the multi-objective fitness function to obtain a target underwater patching material mix ratio. The traditional trial-and-error test method is replaced, the test workload is greatly reduced, and the mix ratio research and optimization efficiency is improved. The engineering adaptability and application reliability of the target underwater patching material mix ratio are ensured, and the core engineering goals of the underwater grouting repair, defect repair and bearing capacity recovery are achieved.

The utility model relates to the technical field of stamping production devices, in particular to a stamping part surface defect repairing device which comprises a control system and a repairing device body and further comprises a self-adaptive clamp, the self-adaptive clamp comprises a base plate, sliding blocks, vacuum suction cups and a locking assembly, the base plate is provided with sliding grooves in a honeycomb array, the sliding blocks are arranged in the sliding grooves in a sliding mode, and the vacuum suction cups are arranged in the sliding grooves. A spring is arranged between the sliding block and the ground surface of the sliding groove, the upper end of the sliding block is connected with a vacuum chuck through a ball-and-socket joint, an annular groove is formed in the side face of the sliding block, an elastic sealing ring is arranged in the annular groove, and a communicating hole is formed in the ground of the annular groove and communicated with an external high-pressure air source through a cavity formed in the sliding block. The spring is flexibly matched with the curved surface of the workpiece, then high-pressure gas acts to drive the locking assembly to act to position the sliding block, and finally the sliding block and a stamping part are connected through the vacuum suction cup, so that the rigid-flexible contradiction of a traditional clamp is solved, the curved-surface workpiece is effectively fixed, and meanwhile the surface of the workpiece is prevented from being damaged.

An embodiment of the present invention discloses an automatic circuit board defect detection method and system based on machine vision to improve the accuracy and efficiency of circuit board defect detection and repair. The method includes: obtaining a surface image data set of a target circuit board; performing image preprocessing operations on the surface image data set to generate a preprocessed image data set; inputting the preprocessed image data set into a pre-trained defect feature extraction model, and performing multi-level feature fusion processing on each image data through the defect feature extraction model to generate a multi-dimensional defect feature set; determining a defect location information set of the target circuit board according to the matching degree calculation result between the multi-dimensional defect feature set and a preset defect feature template; and transmitting the defect location information set to a defect repair control terminal to trigger the defect repair control terminal to generate a repair path planning instruction according to the defect location information set.