Synthetic Discriminant Wiener Filter for In-Process Laser Cutting Quality Control

Abstract

Characteristic spark-cone images are produced beneath the workpiece during reactive gas assisted laser cutting processes. Laser cutting quality is controlled using robust optical pattern recognition and classification of the spark-cone images. High irradiance fully formed spark cones are characteristic of a high quality dross-free cut, whereas a sparse cone indicates a poor quality cut with dross attachment to the lower surface of the workpiece. It was found that by incorporating both the out-of-class image, sparse spark cone, and the in-class image, fully formed spark cone into a Wiener filter construction, the discriminant ability of the imaging control system was significantly enhanced; three out-of-class images gave optimum performance. The Wiener filters formed from spark-cone images, recorded when cutting different thickness materials, were integrated into a synthetic discriminant function (SDF) filter. When spark-cone images of a laser cutting process were cross-correlated with the SDF, it gave high output peaks for a good quality cut, and a low output signal for a poor quality cut (Lugt, 1994; Wang, Chatwin, and Young, 1994; Braunecker, Hauk, and Lohmann, 1979; Casasent, 1984; Huang and Chatwin, 1994).