A prediction-correction scheme for microchannel milling using femtosecond laser

In this paper, a prediction-correction scheme is proposed to online measure and regulate the milling depth of microchannel using an indicator of laser triggered plasma. Firstly, a prediction model, with respect to the laser fluence and feedrate, is established with several calibration tests using the least square fitting method. It is utilized to change the focal position of objective to track the depth evolution of newly generated surface. Meanwhile, a scanning path for every milling layer with an offset in Z-axis at the beginning and the end of the trajectory, is developed to drive the plasma brightness periodically changing. Then, the milling depth could be obtained when the brightness reaches to the maximum value. By doing so, an online measurement method is presented to estimate the milling depth using the trend of plasma brightness. Furthermore, a correction model is developed to iteratively adjust the feedrate with the online estimated depth. Therefore, the microchannel milling process could be monitored and controlled,in a closed-loop manner, in order to accurately regulate the milling depth. Finally, an online measurement and closed-loop microchannel milling is carried out on the self developed micro-machining center. The effectiveness and correctness of the proposed method are verified by comparing the estimated depth with the actually measured results.