Paper Web Imaging with Advanced Defect Classification, 2002 Technology Summit Proceedings

J. Rauhamaa & R. Reinius

Paper web inspection with defect detection and classification helps mills to reduce production disturbances, remove causes of defects, and deliver products of correct quality to the customers. However, the capabilities of conventional inspection systems are limited. The actual severities of spots or holes cannot always be identified precisely enough. Modern imaging systems open up new possibilities. They utilize CCD-camera technology to create electronic gray scale images of the paper. Therefore, the fine details of defects can be discerned, which makes it possible to classify the defects more precisely than before. This is accomplished by various digital image retrieving and analysis techniques. Neural networks can be used for classifying defects which the system has been trained to recognize. For example, differentiating slime holes from small wire holes at a re-reeler helps to prevent paper breaks at an off-line coater. As a result, these modern systems can help the papermaker to enhance mill productivity.