14results about How to "Easy defect detection" patented technology

The invention provides a welding spot defect detection method. The welding spot defect detection method comprises the following steps: S1, acquiring point cloud data of a welding spot; s2, filtering and multi-view point cloud registration are carried out on the obtained point cloud data to obtain complete point cloud data of the welding spots; s3, determining the surface curvature of each point in the complete point cloud data, representing the surface curvature in the complete point cloud data in a color form, and converting the complete point cloud data of the welding spot into an image containing welding spot defect information; and S4, performing welding spot defect identification on the image containing the welding spot defect information by using a welding spot defect detection model based on deep learning to obtain a final detection result. The terminal welding spot defect detection method aims at terminal welding spot defect detection of the aerospace cable connector, can effectively avoid the light reflection problem which cannot be solved by a traditional detection method, and has the advantages of high identification precision and high detection efficiency.

The invention discloses an AOI-based micron-sized defect identification and detection system, and relates to the technical field of defect identification and detection, and the system comprises the following modules: a board type database building module for building a board type database and incorporating images of each bare PCB and each assembled PCB into the board type database; the image value is obtained through the collected image of the PCB, then the image value and the measured value are combined to obtain the judgment coefficient, and whether the PCB is a bare board or an assembled board is judged by comparing the judgment coefficient with the judgment coefficient preset threshold value, so that the recognition accuracy of the PCB is improved, and the recognition accuracy of the PCB is improved by incorporating the judgment coefficient into the board type database. According to the method and the device, the judgment coefficient is obtained, so that the reference plate type image can be subsequently identified in the plate type database according to the judgment coefficient, the PCB can be conveniently subjected to reference comparison, the defects of the PCB can be conveniently identified, the PCB is identified, the defects of the PCB can be subsequently detected in a targeted manner, and the defect identification efficiency can be improved.

The invention discloses a method, device and equipment for detecting defects of a liquid crystal display screen and a storage medium. The method comprises the steps that an effective display area image of the display screen is acquired; repairing a region-of-interest mask of the effective display area image, the region-of-interest mask determining an effective pixel range of the effective display area image for blank pressing defect detection; removing the repaired inner ring image of the interest area mask in the effective display area image to obtain an outer ring image of a preset pixel layer number; unfolding the outer ring image and splicing the outer ring image into a strip-shaped image; and based on the strip-shaped image, detecting the defect of the display screen blank pressing area. By means of the method, the capability of detecting the edge pressing defects of the corner areas of the liquid crystal display screen can be improved.

The invention discloses a detection method, device and equipment based on visual detection of defects and a storage medium, and relates to the technical field of image processing, and the detection method based on visual detection of defects comprises the following steps: obtaining to-be-processed image data and carrying out data preprocessing to obtain defect image data; defect detection processing is conducted on the defect image data based on a defect detection model, surface defect detection data are obtained, a loss function is added to the defect detection model, and the defect detection model is obtained by improving a YOLO model; and screening the surface defect detection data to obtain a surface defect detection result. According to the invention, the accuracy of defect detection is improved.

The application provides a measuring device, and relates to the technical field of optical detection.The measuring device comprises a support assembly, an auxiliary assembly and a detection mechanism.The support assembly comprises a first support frame and a second support frame arranged oppositely; the auxiliary assembly is arranged on the first support frame; at least one avoiding hole is arranged on a fixed plate in the auxiliary assembly; when a contact is placed on the fixed plate, and a weak boundary area of the contact is arranged opposite to the avoiding hole; the detection mechanism comprises an upper light source assembly, a lower light source and a visual detection assembly; the upper light source assembly and the visual detection assembly are arranged on the second support frame; the upper light source assembly is arranged between the auxiliary assembly and the visual detection assembly; the lower light source is arranged on the first support frame and below the fixed plate; and the light of the lower light source can irradiate to the weak boundary area of the contact through the avoiding hole.The measuring device can improve the image definition when detecting the defects of the contacts of Bluetooth earphones, thereby improving the reliability of the detection result.

The application discloses a kind of defect detection devices for plastic furniture production, it is related to defect detection field, it solves the problem that existing defect detection device is easy to cause incomplete detection, including: detection box and belt conveying frame, the top of belt conveying frame is provided with plastic bucket, the top of plastic bucket is provided with two U-shaped frames, the both ends of U-shaped frame bottom are all installed with first laser probe, and top plate is installed between two U-shaped frames;Further including: detection mechanism, for the inside and outside of plastic bucket synchronous detection, detection mechanism is installed in the inside of detection box, and detection mechanism includes mounting bracket installed in the inside of detection box;The application can make top plate do circular motion in the process of moving downward by detection mechanism, and the inside and outside of plastic bucket can be synchronously detected by the first laser probe at the both ends of U-shaped frame, so as to facilitate the inside and outside of plastic bucket synchronous and fast detection.

Embodiments of the present application disclose a chip verification method and device, system, electronic equipment and storage medium, and relate to the technical field of electronic design automation, which can give full play to the large-scale and rapid verification advantages of a hardware verification platform while facilitating defect detection. The method is based on a hardware verification platform and includes: running a hardware simulation program of a chip to be verified; sending behavior information and behavior result information of the chip to be verified in program running to a software verification platform according to a preset strategy, so that the software verification platform verifies and reviews the chip to be verified according to the behavior information and the behavior result information. The present application is applicable to various chip verifications.

The invention relates to a straw defect detection method and system based on visual identification, and relates to the field of straw production technologies, and the method comprises the steps: obtaining an infrared detection image of a straw at a preset shooting point; acquiring the detection pixel chroma of each pixel point in the infrared detection image, defining the pixel points of which the detection pixel chroma is within a preset required chroma range as normal pixel points, and defining the pixel points except the normal pixel points as abnormal pixel points; concluding adjacent abnormal pixel points into the same preset pixel set which is initially empty; counting according to abnormal pixel points in each pixel set to determine the number of set pixels; and defining a pixel set of which the set pixel number is greater than a preset reference pixel number as a foreign matter feature set, and determining an area formed by abnormal pixel points contained in the foreign matter feature set as a foreign matter area. The suction tube defect detection device has the effect of improving the detection effect of suction tube defect detection.

The utility model provides an anti-seizure emptying mechanism for seamless steel pipe processing relates to emptying mechanism field, including: pushing mechanism and blanking mechanism, the pushing mechanism is provided in the front side of blanking mechanism, and the right side of pushing mechanism is provided with pipe mill, blanking mechanism includes trough plate, and the trough plate is provided with the pipe mill. An inclined plate is connected between the groove plate and a bearing plate included by the pushing mechanism, a through hole groove is formed in the bottom of a groove cavity in the groove plate, the discharging mechanism further comprises a swing rod assembly located on the outer side of the groove plate, the swing rod assembly comprises a U-shaped frame hinged to the outer wall of the groove plate, and an eccentric wheel is slidably connected to the lower side of the U-shaped frame. An electric push rod is installed on the left side of the bearing plate, and a limiting groove is formed in the upper side of the bearing plate. The seamless steel tube emptying mechanism solves the problems that an existing seamless steel tube emptying mechanism still has the phenomenon that emptying is stuck or scattered, and surface defects of tubes are inconvenient to detect.

The present invention belongs to the technical field of industrial profile detection, and specifically discloses an industrial profile defect detection device based on computer vision, comprising a workbench, a support frame is fixedly connected to the top of the workbench, an industrial computer is arranged on one side of the workbench, and a uniformly distributed support table is fixedly connected to the top of the workbench; by setting a first detection component, an electric push rod is started to drive a mounting plate to move to the opening height of an internal groove of the profile, and by starting a linear slide rail, the mounting plate can be driven to move synchronously by the electric push rod, so that it can move into the internal groove of the profile, and in this process, the profile surface can be supplemented with light by starting a first LED lamp, and in this process, the light path formed by the light of the first LED lamp after being reflected by a reflector can supplement light for the blind spot of the internal groove of the profile, so that a second industrial camera can shoot the blind spot of the internal groove of the profile, thereby avoiding the poor shooting effect at the blind spot during the traditional profile detection process.

This invention discloses a machine vision-based laser chip surface defect detection device, comprising a chip conveying system, an image acquisition system, and a chip acquisition platform. The chip conveying system transports a waffle box containing chips to the chip acquisition platform. The image acquisition system acquires images of each chip individually. The chip acquisition platform inspects the chips and classifies defective and non-defective chips accordingly. This invention achieves automated surface defect detection of laser chips and filters out defective chips.

The invention belongs to the technical field of industrial profile detection, and particularly discloses an industrial profile defect detection device based on computer vision, which comprises a workbench, the top of the workbench is fixedly connected with a support frame, one side of the workbench is provided with an industrial computer, and the top of the workbench is fixedly connected with uniformly distributed support tables; by arranging a first detection assembly, an electric push rod is started to drive a mounting plate to move to the forming height of a groove in the profile, a linear sliding rail is started to drive the mounting plate to move synchronously through the electric push rod, the mounting plate can move into the groove in the profile, and in the process, light can be supplemented to the surface of the profile by starting a first LED lamp; in the process, light rays of the first LED lamp are reflected by the light reflecting plate to form a light path, light can be supplemented to dead corners of the grooves in the profiles, the dead corners of the grooves in the profiles can be conveniently shot by the second industrial camera, and the situation that the shooting effect at the dead corners is poor in the traditional profile detection process is avoided.

The invention discloses a chip abnormal defect identification method based on multi-template fusion and a storage medium. The method comprises the following steps: step 1, constructing a chip defect detection model based on deep learning; step 2, collecting each type of chip image; 3, based on median fusion, obtaining an ideal chip image of each type of chips; step 4, carrying out image difference; step 5, performing sliding cutting on the difference image to obtain chip difference images with the same size and overlapped set sizes; step 6, training a chip defect detection model; step 7, performing differential operation and sliding cutting on the to-be-detected chip image; step 8, predicting a chip defect type and a defect position in a corresponding set chip difference image by using the trained chip defect detection model; and finally, determining the position of the defect in the original to-be-detected chip according to the difference image number of the chip with the set size. According to the invention, the appearance difference between chips of different models can be reduced, the universality of the model is improved, and the defect identification precision is high.