Cross-Correlation-Based Algorithm for Monitoring Laser Cutting With High-Power Fiber Lasers

We report on an innovative algorithm for an InGaAs and Si photodiode-based sensor system to detect incomplete cuts during high-power near infrared fiber laser cutting. Using such dual-photodiode-based sensor, the thermal radiation from the process zone is measured with the diode current being digitalized with a sampling rate of 20 kHz. The algorithm encompasses a normalization of the measured current, digital filtering, and cross-correlation calculation of both filtered diode signals. This sensor approach allows us to successfully detect cut interruptions in a series of more than 100 cuts in stainless steel, mild steel, and aluminum of different thicknesses with a type I and type II error of 0%. The underlying physics of the detection scheme based on the changes of the dynamic melt flow in the cut kerf from a complete cut to an incomplete cut is discussed.