[AI Image Inspection Case] Detection of Foreign Objects in Cylindrical Filters
Detects foreign substances (fibers, dust, hair, and particulate matter) in cylindrical filters.
In visual inspections conducted by workers, there is often variability in the criteria for determining "good products" and "defective products" among inspectors, and the more ambiguous the criteria, the more inconsistent the inspection results tend to be. Please consider a stable and efficient inspection using an image inspection system. The image on the left shows the environment with the camera, lens, and lighting. The image on the right depicts the task known as "annotation," which involves framing the areas to be detected. By "training" the framed areas, we were able to detect the target objects within the inspection images. The inspection items were placed on a rotating platform, and detection verification was conducted while rotating. During the verification, it was assumed that the inspection would take about 60 seconds per item. As for dust, it could not be visually confirmed as defective, so settings and detection could not be performed. If defective parts cannot be photographed, the inspection becomes challenging. Creative solutions are needed for capturing images.
basic information
【Software and Equipment Used】 Software Used: DeepSky Field of View: Approximately 248 x 197mm Minimum Size of Inspection Target: 2mm Number of Inspection Points: 1 location to find defects across the entire screen Camera Resolution: 1.3 million pixels Lens Focal Length: 8mm Distance Between Lens and Product: Approximately 300mm
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