Multi-Objective Optimization of Laser Cleaning Quality of Q390 Steel Rust Layer Based on Response Surface Methodology and NSGA-II Algorithm

To improve the laser cleaning surface quality of rust layers in Q390 steel, a method of determining the optimal cleaning parameters is proposed that is based on response surface methodology and the second-generation non-dominated sorting genetic algorithm (NSGA-II). It involves constructing a mathem...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Materials 2024-06, Vol.17 (13), p.3109
Hauptverfasser:	Wang, Guolong, Deng, Jian, Lei, Jieheng, Tang, Wenjie, Zhou, Wujiang, Lei, Zeyong
Format:	Artikel
Sprache:	eng
Schlagworte:	Advanced manufacturing technologies Carbon Carbon steels Cleaning Corrosion resistance Experiments Genetic algorithms Laser beam welding Lasers Morphology Multiple objective analysis Nuclear power plants Optimization Oxygen content Process parameters Repetition Response surface methodology Rusting Scanning electron microscopy Sorting algorithms Steel Surface properties Surface roughness Surface treatment Variance analysis Welding parameters
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!