Image Processing Algorithm for In Situ Monitoring Fiber Laser Remote Cutting by a High-Speed Camera

Abstract

We present an in situ process monitoring approach for remote fiber laser cutting, which is based on evaluating images from a high-speed camera. A specifically designed image processing algorithm allows the distinction between complete and incomplete cuts by analyzing spectral and geometric information of the melt pool from the captured images of the high-speed camera. The camera-based monitoring system itself is fit to a conventional laser deflection unit for use with high-power fiber lasers, with the optical detection path being coaxially aligned to the incident laser. Without external illumination, the radiation of the melt from the process zone is recorded in the visible spectral range from the top view and spatially and temporally resolved. The melt pool size and emitted sparks are evaluated in dependence of machining parameters such as feed rate, cycles, and focus position during cutting electrical sheets.

Design and Development of a Multisensory Real-Time Monitoring Platform for Ultrafast Laser Engraving Process

“…Using these types of cameras, changes in the keyhole or shape of the melt pool can be measured [17], [36]. Various studies have been conducted on the use of high-speed cameras to monitor laser welding, laser cutting, and laser additive manufacturing [37], [38], [39], [40]. In this study, a high-speed camera was assessed to monitor the laser scribing process.…”

Predicting and Enhancing the Multiple Output Qualities in Curved Laser Cutting of Thin Electrical Steel Sheets Using an Artificial Intelligence Approach

“…Furthermore, laminates with a wider kerf result in a larger core loss [3]. In addition, the recast layers may rejoin during laser cutting, closing the kerf and causing re-welding [5,6].…”

“…The efforts to optimize cut quality in electrical steel sheets, including HAZ, kerf width, and re-welded portion, have been conducted in several studies [4,5,[7][8][9]. Nguyen et al [4] and Rohman et al [7] minimized the HAZ and kerf width, respectively, by optimizing the laser process parameters for straight cuts of non-oriented electrical steel sheets.…”

“…By controlling the working temperature during laser cutting, Nguyen et al [8] reduced the kerf width and HAZ of straight cuts of electrical steel sheets. A laser process parameter optimization technique based on image processing was used to eliminate re-welded cuts in the circular cutting of electrical steel sheets [5].…”

Statistical Analysis of Gyroscopic Data to Determine Machine Health in Additive Manufacturing

“…Researchers have conducted extensive investigations into using various sensors, including accelerometers [42][43][44], cameras [45,46], acoustic emission sensors [47,48], and thermocouples [49][50][51][52], for in situ monitoring. Through these studies, it has been consistently observed that employing in situ monitoring techniques enables the prediction of the health condition of 3D printers and facilitates the detection of defects in the quality of the printed products.…”