Accuracy and repeatability estimation in micromachining using an enhanced artificial vision algorithm for controlling the screen LED positioning on a LCD screen

Study of micromachining systems have become an important area of interest over the last decades. Within this issue, the closed-loop positioning systems play an important role when high machining precision should be fulfilled. In this proceeding, the vision control system of a demonstrator used in a former research workytpooo is improved in order to achieve better accuracy and repeatability results on the micro-machine tool. In this demonstrator an improved camera objective is mounted so that it jointly moves with a XY micromachine platform. The aim of the camera is to capture the image of a given LED, which is turned on a 326 ppi smartphone in order to serve as a coordinate position of the cutting tool path. The current study differs from a former camera-screen research in using an enhanced algorithm which is capable to work out the position of two lighted LEDs, which are uniquely detached by a LED gap, thus improving the resolution of the closed-loop control system. The developed artificial vision algorithm uses an advanced filtering method to detect and improve the light intensity and shape form of the captured image of the lighted LED. Having obtained the estimated position of the LED within the machining limits of the smartphone screen, the closed loop system is tested by a Back Step Test in order to evaluate the precision and repeatability of the micromachine tool. A significant accuracy improvement in micromachining positioning systems has been assessed, thus illustrating the viability of the enhanced artificial vision algorithm.