1. ANN Prediction of Laser Power, Cutting Speed, and Number of Cut Annual Rings and Their Influence on Selected Cutting Characteristics of Spruce Wood for CO2 Laser Processing
- Author
-
Ivan Ružiak, Rastislav Igaz, Ivan Kubovský, Eugenia Mariana Tudor, Milada Gajtanska, and Andrej Jankech
- Subjects
CO2 laser ,artificial neural networks ,spruce wood ,cutting kerf ,heat-affected zone ,sensitivity analysis ,Technology ,Electrical engineering. Electronics. Nuclear engineering ,TK1-9971 ,Engineering (General). Civil engineering (General) ,TA1-2040 ,Microscopy ,QH201-278.5 ,Descriptive and experimental mechanics ,QC120-168.85 - Abstract
In this work, we focus on the prediction of the influence of CO2 laser parameters on the kerf properties of cut spruce wood. Laser kerf cutting is mainly characterized by the width of kerf and the width of the heat-affected zone, which depend on the laser power, cutting speed, and structure of the cut wood, represented by the number of cut annual rings. According to the measurement results and ANN prediction results, for lower values of the laser power (P) and cutting speed (v), the effect of annual rings (ARs) is non-negligible. The results of the sensitivity analysis show that the effect of v increases at higher energy density (E) values. With P in the range between 100 and 500 W, v values between 3 and 50 mm·s−1, and AR numbers between 3 and 11, the combination of P = 200 W and v = 50 mm·s−1, regardless of the AR value, leads to the best cut quality for spruce wood. In this paper, the main goal is to show how changes in the input parameters affect the characteristics of the cutting kerf and heat-affected zones for all possible input parameter values.
- Published
- 2024
- Full Text
- View/download PDF