63 results about "Visual defects" patented technology

The invention discloses a printed circuit board withstand voltage detection and evaluation method, which comprises the following steps: in the whole withstand voltage detection process, aiming at different process batches and environments, acquiring electrical signals, process parameters, environment variables and multi-modal visual data, and carrying out time sequence synchronization marking and standardized preprocessing; extracting multi-source features by using a feature coding algorithm, and establishing a multi-mode distribution model covering signal mutation, visual defects and working condition anomalies; through cross-modal feature fusion and a time sequence causal inference model, an abnormal event causal relationship graph is automatically constructed, and a voltage withstanding failure root cause chain is identified and positioned; according to the method, the efficient structured management of the detection data, the accurate traceability of the abnormal reasons and the cross-batch analysis are realized, and the capability of diagnosing and preventing the withstand voltage abnormality of the printed circuit board is remarkably improved.

The invention provides an energy storage device damage diagnosis and interaction system based on penetration vision and a large model, and relates to the technical field of energy storage device damage diagnos.The energy storage device damage diagnosis and interaction system comprises a penetration type 3D sensing module, a periodic topology analysis module, a feature mapping and retrieval module and a large model reasoning and interaction module, and the energy storage device is scanned and reconstructed; the method comprises the following steps: constructing a time-space decoupling periodic Transform network, introducing a periodic mask matrix to force the network to pay attention to a repeatability rule of an internal structure of a battery, and identifying internal tiny deformation and structural damage by calculating topological consistency under the condition that a large amount of negative sample training is not needed; visual defect features are mapped into text embedding by utilizing a feature projection technology, a diagnostic report containing physical cause analysis and maintenance suggestions is generated by combining a retrieval enhancement generation technology and a large language model, and a user is supported to perform interactive questions and answers in a natural language. The method can solve the problems that in the prior art, three-dimensional deformation is difficult to quantify, small samples are difficult to train, and intelligent decision-making ability is lacked.

The invention discloses a visual defect identification and evaluation method for aviation I-shaped edge strip processing quality, particularly relates to the field of machine vision detection and discrimination, and is used for solving the problem of mistaken elimination or length measurement distortion caused by easy confusion of end part short region slender defects and end surface mirror reflection secondary images. The method comprises the following steps: establishing part local coordinates and fillet belt unfolding coordinates; screening a main evaluation view angle and a dual view angle and generating a displacement prediction window; extracting a candidate slender response set through dual-view collection and local registration; calculating a mapping residual distance and a same shift segment length and generating a mirror pseudo coefficient; and executing gating judgment and mirror image mask removal or length measurement and category judgment, and binding and storing to finish evaluation.

The application belongs to the technical field of optical lens detection, and particularly relates to an optical lens appearance defect detection device, which comprises a supporting assembly, a feeding device is installed on the supporting assembly, a first discharging slide plate is installed at the discharging end of the feeding device, a mounting seat is fixedly connected to the supporting assembly below the first discharging slide plate, supporting rollers are rotationally connected to both ends of the mounting seat, and the cooperation of the structures such as the belt ring, the first visual defect detection camera, the pushing cylinder, the guide plate and the driving roller is achieved, so that after the optical lens is accurately positioned in the positioning groove formed in the belt ring, the first visual defect detection camera arranged on both sides is used to detect the end of the optical lens, then the pushing cylinder is used to push the optical lens to the driving roller, the driving roller is rotated to drive the optical lens to slowly rotate, the second visual defect detection camera is used to detect the circumferential side of the optical lens, and the mechanical hand is not needed to be used for carrying and aligning, so that the detection efficiency is greatly improved.

The application relates to the technical field of machine vision and image processing, and discloses a plastic valve visual defect real-time detection method and system based on deep learning, which comprises the following steps: acquiring a gray image containing a plastic valve, positioning the centroid of a plastic valve main body area by using geometric moments; converting the gray image to a polar coordinate based on the centroid, applying one-dimensional high-pass filtering, and determining a dynamic segmentation threshold to extract abnormal gray pixel points; performing spatial density clustering after reverse mapping to determine a suspected defect area; calculating the Euclidean distance between the centroid of the suspected defect area and the centroid of the plastic valve main body area, synchronously inputting the distance and image features into a double-input convolutional neural network to output a plastic valve defect detection result. The application filters out cloud and fog-shaped diffuse reflection interference, and improves the accuracy of defect detection.

The invention relates to a visual aid (1) comprising at least one imaging optic (2) with variable focal length for positioning between a viewer's eye and a scene to be viewed, further comprising means for controlling the change in focal length of the at least one imaging optic, optoelectronic means (3) for determining the distance of the imaging optic (2) optionally from one or more nearest objects in the scene to be viewed in the viewing direction of the viewer's eye and / or with a selectable angular tolerance around the viewing direction of the viewer's eye, electronic means for controlling the means for controlling the change in focal length of the at least one imaging optic (2), wherein said determined distance is converted into a target focal length of the at least one imaging optic (2) by means of a table of values ​​and / or by means of an equation.as well as an energy source for the aforementioned optoelectronic and electronic means and the means for control. The invention further relates to a method for vision correction and a computer program.

The application discloses a kind of based on improved AnoGAN small sample substation equipment visual defect detection method, belong to machine learning technical field;The method comprises: obtaining training substation equipment image;According to normal substation equipment image training AnoGAN adversarial generation network;Defect substation equipment image is input into AnoGAN adversarial generation network after training is completed;After pre-processing, defect substation equipment image is input into pre-training similarity classification network and is classified;After pre-processing, defect substation equipment image is input into pre-training convolution classification network and is classified;According to similarity classification result and convolution classification result, obtain defect detection result.The application also provides a kind of based on improved AnoGAN small sample substation equipment visual defect detection system.The network of the application is trained to normal data for training, so its generation effect can be distinguished to all non-normal state equipment, and the practical application is more widely used.

The application discloses a kind of wind power blade defect detection method and system, it is related to defect detection technical field, the system includes: external data acquisition module, state evaluation module of lightning arrester, inner cavity check mapping module, inner cavity image acquisition module, inner cavity defect evaluation module, blade health evaluation module.The application generates internal key check area instruction based on external defect coordinates, guides inner cavity detection equipment to carry out fixed-point review, improves the pertinence and efficiency of inner cavity detection;At the same time, by fusing lightning arrester electrical performance data and visual defect information, and the defects in space are associated with correction, the specificity of lightning damage is realized, the accuracy and reliability of wind power blade health state comprehensive evaluation are improved, the problems that the internal detection blindness is large, the efficiency is low in the prior art, and the defect cause judgment is single, and lightning damage and ordinary defects cannot be accurately distinguished.

This invention belongs to the field of machine vision inspection, specifically relating to a deep learning-based visual defect detection system for injection-molded shells of high-end equipment. The system includes: a biomimetic compound-eye programmable optical imaging subsystem for generating a reverse compensation light field based on surface morphology to achieve feature enhancement and noise stripping; a production process perception module for monitoring environmental parameters and extracting state feature vectors; a cloud-based adaptive learning center for constructing a meta-learning model and generating specific adaptation parameters; and an edge-side multi-task inference terminal for receiving dynamic knowledge distillation results and performing defect localization and pixel-level segmentation. This invention, through physical imaging and algorithmic collaboration and a cloud-edge architecture, suppresses optical overflow and solves the model adaptation problem under production fluctuations, improving processing efficiency while maintaining accuracy, and achieving closed-loop optimization and continuous evolution of the system.

The invention relates to a method for manufacturing a customized optical element to adjust an optical property of an optical component, such as goggles, wherein the method comprises the steps of receiving customer data indicative of a visual defect a person and / or a desired visual correction of the optical component; determining, from the customer data, the shape of a first surface of an optical element to be manufactured, such that the optical component, when the optical element is applied to an optical surface of the optical component, compensates at least partially or entirely the visual defect of the person or exhibits the desired visual correction; manufacturing the optical element using a liquid material that when brought in shape, is solidified.

The utility model relates to the technical field of visual detection, in particular to visual defect detection equipment which comprises a workbench, a protective cover covering the workbench, a backlight plate fixed on the workbench, a clamp installed on the workbench and a visual camera assembly arranged above the workbench. The detection driving assembly is used for driving the visual camera assembly to move left and right, the protective cover is installed on the workbench, the detection driving assembly is installed on the inner side of the top of the protective cover, the clamp is used for clamping and positioning a product on a backlight plate, and a controller is arranged on the protective cover; the device can detect the defects of uneven density, holes, scratches, smudginess, pits and the like on a product, avoids the situation that the defects of the holes, the pits and the like are not observed, and ensures the quality of the product.

This utility model relates to the field of automotive seat processing technology, specifically to an automotive seat visual defect detection device. It includes a base, a servo motor that outputs controllable torque to drive the entire moving assembly to perform detection movements, and a camera that collects image data of the automotive seat surface for subsequent defect analysis. This automotive seat visual defect detection device smoothly transports the automotive seat to the detection area below the protective cover via a conveyor belt. The servo motor drives a gear and a gear ring to precisely mesh, causing the camera to reciprocate in a circular motion along a guide ring. This innovative motion method overcomes the blind spot problem inherent in traditional straight-line detection. The combined design of the connecting frame and damper effectively suppresses the impact of mechanical vibration on image quality. The annular protective cover, combined with the lower slot structure, protects the internal components while ensuring an open detection field of view. Compared to fixed-point detection schemes, this design improves detection coverage.

The invention belongs to the technical field of optical lens detection, and particularly relates to an optical lens appearance defect detection device which comprises a supporting assembly, a feeding device is installed on the supporting assembly, a first discharging sliding plate is installed at the discharging end of the feeding device, and a mounting base is fixedly connected to the portion, below the first discharging sliding plate, of the supporting assembly. The belt ring, the first visual defect detection camera, the material pushing air cylinder, the material guiding plate, the driving roller and other structures are arranged in a matched mode, so that the optical lens is accurately positioned in a positioning groove formed in the belt ring; the first visual defect detection cameras arranged on the two sides are used for carrying out defect detection on the end portion of the optical lens, then the pushing air cylinder is used for pushing the optical lens to the driving roller, the driving roller rotates to drive the optical lens to rotate slowly, and the peripheral side of the optical lens is detected in cooperation with the second visual defect detection cameras. A manipulator is not needed for carrying and aligning, so that the detection efficiency is greatly improved.

The invention provides a method and a system for quickly establishing a visual defect library. The method comprises the following steps: irradiating a sample by using a first visible light beam and marking the sample as an initial marking area; on the basis of the initial labeling area, irradiating by using a second visible light beam and removing an irradiated area of the second visible light beam from the initial labeling area in real time to obtain an ROI labeling result; adjusting light source parameters and image acquisition angles, repeating the irradiation marking step, and acquiring enhanced sample images under different light source parameters and different angles; and a training data set is constructed based on the sample image and is used for training an image detection model. According to the method, the ROI region of the sample is pre-labeled in the data acquisition stage through the visible light beam device, so that the data labeling cost and the post-processing difficulty are effectively reduced, the deviation problem of automatic labeling of a diffusion model is avoided, and efficient and reliable rapid establishment of a visual defect library is realized.

The application relates to the technical field of industrial visual inspection, and discloses a kind of intelligent visual defect detection methods for plastic product production, comprising: based on the continuous texture direction formed by fusion material itself in the weld area image, texture reference structure with sparse topological constraint is constructed;According to the texture reference structure, the weld area image is locally textured element deconstruction, and the texture element space layout embedded in the texture reference structure constraint is obtained;According to the texture reference structure, the topological structure of the texture element space layout in the weld area image is predicted, and the topological abnormal area meeting the texture neighborhood self-correction mechanism is determined;According to the spatial topological correlation between the topological abnormal area and the texture reference structure, the real defect area is extracted;The application realizes the accurate and reliable detection of the defect of the weld area of the plastic product by texture topological structure constraint and spatial layout self-correction, effectively improves the stability and accuracy of the weld quality control.

This invention discloses a method for extracting and identifying visual defect features of impact-resistant power safety warning facilities, belonging to the field of intelligent power facility inspection technology. The method includes acquiring image sequences of facilities and environmental state parameters in an outdoor environment; deconstructing the images into physical and apparent states to obtain deconstructed images of components such as the outer shell, reflective coating, and printed markings; performing pixel-level difference analysis between these images and a standard template to generate an anomaly difference map. A facility health degradation model is constructed based on the correlation between environmental parameters and the difference map. Under the guidance of this model, iterative feature focusing calculations are performed on the difference map to extract multi-scale visual defect feature vectors corresponding to impact damage patterns. Based on these feature vectors, defect matching decisions are made, outputting specific defect types and location information. This invention achieves accurate identification of impact damage and health status assessment of warning facilities in complex environments.

The invention relates to a method for manufacturing a customized optical element to adjust an optical property of an optical component, such as goggles, wherein the method comprises the steps of receiving customer data indicative of a visual defect a person and / or a desired visual correction of the optical component; determining, from the customer data, the shape of a first surface of an optical element to be manufactured, such that the optical component, when the optical element is applied to an optical surface of the optical component, compensates at least partially or entirely the visual defect of the person or exhibits the desired visual correction; manufacturing the optical element using a liquid material that when brought in shape, is solidified.

The invention provides a visual compatibility problem auxiliary detection method, system and device and a storage medium, relates to the technical field of visual compatibility problem detection, and solves the technical problem that a detection method in the prior art cannot directly and effectively detect visual defects. The method comprises the following steps: processing an application operation video by adopting a continuous visual feature extraction and visual consistency comparison method to obtain visual defect data of a to-be-detected application in a to-be-tested environment; according to the visual defect data, manual evaluation is carried out, and a visual compatibility problem auxiliary detection result for the to-be-detected application is given. According to the invention, visual defects which are not easily perceived by naked eyes of testers can be detected, and the testing efficiency of application testing is improved.

The invention belongs to the technical field of defect detection, and provides a zero-sample visual defect rapid detection method based on a core set strategy, which comprises the steps of image acquisition and preprocessing, multi-scale feature extraction, initial core set construction, core set expansion and screening, and similarity scoring. According to the method, the small-scale core set is introduced into the zero sample scene, so that the time performance of the algorithm in the actual working scene is improved, and the real-time performance is guaranteed; an initial core set is obtained through a sparse downsampling method, feature distribution information can be represented more accurately and fully, and it is ensured that core set features obtained from the interior of test data can be closer to overall real distribution of the test data; the general distribution rule of the defect features in the test data is extracted, and whether the data defects exist or not is evaluated according to the general distribution rule, so that the dependence of a conventional zero sample method on external source data information is avoided, and the generalization and robustness of the method are effectively improved.

This application discloses a method and system for visual defect detection in surface mount technology (SMT) manufacturing, relating to the field of visual inspection technology. The method includes the following steps: acquiring characteristic information of the light response of each component on a printed circuit board (PCB); determining the lighting configuration of the area where each component is located based on the characteristic information; switching lighting conditions according to the lighting configuration within a single inspection cycle and acquiring multiple original images of the PCB; performing a fusion process on the multiple original images, including evaluating the brightness, contrast, and saturation of each pixel in the multiple original images to obtain evaluation results, assigning fusion weights to each pixel in the original images based on the evaluation results, and performing weighted fusion of the multiple original images according to the fusion weights to generate a composite image; extracting defect information of each component based on the composite image and determining defects based on the defect information. This application can accurately identify and determine real manufacturing defects, reducing false alarm rates and false negative rates.

This invention discloses a method and system for determining defects in liquid crystal displays (LCDs) based on visual defect feature encoding, belonging to the field of machine vision inspection and image data processing technology. The method includes the following steps: acquiring a brightness image of the LCD under a lit detection screen and generating a brightness residual map; determining a target connected component based on the brightness residual map, and generating a defect master anchor point and an anchor point tolerance set within the target connected component; establishing a ring structure on the brightness residual map centered on the defect master anchor point and each anchor point in the anchor point tolerance set; extracting defect feature encoding based on the ring structure; using the defect feature encoding corresponding to the defect master anchor point as a reference encoding; and comparing the difference between the defect feature encoding corresponding to each anchor point in the anchor point tolerance set and the reference encoding. This invention solves the problem in existing technologies where uneven brightness and weak, gradually changing defect boundaries cause fluctuations in the candidate boxes output by target detection during re-inspection, leading to encoding non-reproducibility and resulting in judgment jitter and inconsistency.

An aerosol generating article comprising a filter and an aerosol generating rod. The filter comprises at least one filter segment. The filter segment comprises a filter media, which contains a liquid additive and at least one filter wrapper. The filter wrapper can be for example a plug wrap. The filter wrapper extends from a first end to a second end of the filter for wrapping the filter media.

The invention discloses corrugated pipe extrusion equipment, and relates to the technical field of corrugated pipe extrusion, the corrugated pipe extrusion equipment comprises an extruder, a base, a support frame and a chassis, and the side wall of the top end of the base is fixedly connected with a traction assembly used for pulling a corrugated pipe extruded by the extruder. According to the invention, the visual defect detector can be driven to realize 360-degree all-round continuous detection on the bulge of the corrugated pipe, and compared with a traditional fixed point detection mode, the detection coverage is more comprehensive, and hidden defects can be effectively prevented from being omitted; the angle of the mounting ring is adjusted through a second motor, and the detection distance is adjusted through a first electric telescopic rod, so that the structure characteristics of corrugated pipe bulges of different specifications can be accurately adapted, and the detection accuracy is improved; meanwhile, the marking spray gun can mark the flaws instantly when the flaws are detected, so that workers can position and cut the flaws conveniently and quickly, the risk that the flaws flow into subsequent procedures is effectively reduced, and the quality of finished products is guaranteed.

The invention provides a new energy motor power assembly visual defect detection system and method based on deep learning, a storage medium and a computer program product. The method comprises the following steps: acquiring an image of a key area of a motor power assembly workpiece; constructing and deploying a deep learning large model for defect detection of the new energy motor power assembly; and performing defect detection and result judgment on the motor power assembly workpiece based on the acquired image and the model deployed by the deep learning large model training and deployment module. The problems that existing manual detection efficiency is low, and traditional machine vision flexibility is poor are solved. The motor power assembly key area image quality is ensured through multi-angle shooting and adaptive illumination, the defect classification, positioning and segmentation precision is improved through a multi-task learning head, high-confidence-coefficient defects are inferred and screened in real time, automatic judgment and unqualified product sorting are achieved through a linkage execution unit, mistaken judgment and missing judgment are reduced, the detection efficiency and the automation level are improved, and the detection efficiency is improved. And the quality control requirements of industrial continuous production are met.

The present invention relates to a method for manufacturing a custom optical element to adjust the optical properties of an optical component, such as a goggle, where the method comprises the steps of: receiving customer data indicative of a visual defect of an individual and / or a desired visual correction of the optical component; determining a shape of a first surface of an optical element to be manufactured from customer data such that when the optical element is applied to an optical surface of an optical component, the optical component at least partially or fully compensates for a visual defect of the individual or exhibits a desired visual correction; the optical element is fabricated using a liquid material that cures after being shaped.

An optical system includes a display configured to display an image and including an eyepiece for observing the image. The eyepiece includes a first lens group and a second lens group. An intermediate pupil is arranged between the first lens group and the second lens group. The second lens group is configured to image the image displayed by the display into the intermediate pupil. The first lens group is configured to image the image arranged in the intermediate pupil into a spatial region. The intermediate pupil and the spatial region are conjugate to one another. A filter unit and / or a wavefront manipulator is / are arranged at the intermediate pupil.

This invention discloses a virtual pre-evaluation method and system for visual assistive devices based on spatiotemporal pathological features. The method includes: acquiring pathological parameters and constructing a virtual scene; generating a sensitivity mask, frequency band loss coefficients, and temporal contrast sensitivity model parameters; performing field-of-view cropping and resampling, dynamic range mapping, local contrast enhancement, edge enhancement, and temporal resampling on the input image when the visual assistive device model is enabled to obtain the image to be processed; performing spatial frequency degradation processing, temporal contrast modulation processing, and visual defect area perceptual filling processing on the image to be processed to obtain the target output image; and collecting the task execution results of the target output image in a standardized virtual task and outputting the evaluation results. This invention can quantitatively pre-evaluate the assistive effect of visual assistive devices without a physical prototype.

The utility model discloses a kind of visual inspection devices for removing defective products, including side stand and visual inspection equipment ontology, the side stand of two side positions is uniformly combined with the vertical displacement adjusting assembly of being provided, and the vertical displacement adjusting assembly of two side positions is uniformly combined with the visual inspection equipment ontology of being provided in the end portion of being close to each other. Advantageous effect lies in: the utility model is through the vertical sliding cooperation of cooperation seat and cooperation groove of dismounting combination component and the transverse sliding cooperation of limiting rod and limiting hole, side stand, vertical displacement adjusting assembly and visual inspection equipment ontology can be disassembled and combined in the side of conveying belt equipment, the combination mode of side stand, vertical displacement adjusting assembly and visual inspection equipment ontology in the side of conveying belt equipment is simple and easy to realize, and then it is convenient to fix side stand, vertical displacement adjusting assembly and visual inspection equipment ontology in the side of conveying belt equipment, and then visual defect detection operation is carried out to rotary bottle.

The application discloses a kind of bamboo board defect detection method and system, it is related to plate detection field, the method includes obtaining the target image of bamboo board to be detected, according to target image, based on image defect detection model, the visual defect range and visual confidence of bamboo board to be detected are determined;Obtain the multiple ultrasonic echo signals of bamboo board to be detected in multiple detection regions, according to multiple ultrasonic echo signals, the multiple ultrasonic confidence corresponding to multiple detection regions of bamboo board to be detected in multiple detection regions is determined, multiple detection regions and multiple ultrasonic echo signals one-to-one correspond;According to visual defect range, visual confidence, multiple detection regions and multiple ultrasonic confidence, the defect confidence of bamboo board to be detected in multiple detection regions is determined;According to the defect confidence of multiple detection regions, the defect detection result of bamboo board to be detected is determined.The application can improve the defect detection efficiency and accuracy of bamboo board.