A machine vision detection algorithm for laser-cutting spark jet angle.

A key radiation sources during the laser-cutting process is sparks, the spark jet angle is closely related to the quality of laser-cutting. A new approach to extract the angle of laser-cut spark jets in industrial metal-cutting processes is presented based on an established machine vision platform. This research demonstrated the algorithm and key theory of PCA and its use in image-processing. The laser-cutting experiment carried out on an St12 steel, the spark images captured during real-time operation are analysed by using the proposed algorithm to obtain the angle and shape of spark jets: the cutting kerf is analysed by optical microscope to acquire the kerf width and associated features. The quantifiable link between sparks angle and kerf width is testified by tests on 1.8-mm thick St12 steel plate, and the results conform to the rules associated with the laser-cutting of metal.