Signal classification for automatic industrial inspection

Details of a system designed to inspect web-type products are presented. The sensing device used is a laser scanner, and a brief description of the scanner is given. A set of bandpass filters is proposed as feature extracters. The required characteristics of the filters are determined through digital simulation, using feature selection methods. The linear classifier is designed from a set of training signals. Contextual information is used in the classification of signals into good product or into various defective categories. In addition, results of a study on inspection of magnetic tapes and abrasive sheets are described.