Analysis of the Laser Forming of Shaped Surfaces Using the Adaptive Neuro-fuzzy Technique
Апстракт
Three-dimensional (3-D) shape modelling from a flat sheet by lasers needs numerous irradiations along surface paths with different parameters of heating. In this study it was attempted to form a three-dimensional shaped surface by laser. The main aim of the study was to analyse the impact of various machining parameters like laser power, scan speed and spot diameters on the surface modelling process. Adaptive neuro-fuzzy inference system (ANFIS) and variable selection procedure was used in order to determine the parameters influence on the surface heights prediction. The selection procedure was done to obtain the found the process parameters which has the highest influence on the surface heights. The method can produce results to simplify the surface heights prediction.
Кључне речи:
Yb fibre laser / variable selection / surface modelling / laser operating parameters / laser forming / AISI 304 stainless steel / Adaptive neuro-fuzzy inference system (ANFIS)Извор:
Lasers in Engineering, 2018, 40, 4-6, 333-340Издавач:
- Old City Publishing
Колекције
Институција/група
Mašinski fakultetTY - JOUR AU - Jović, Srdjan AU - Skulić, A. AU - Lazarević, Mihailo PY - 2018 UR - https://machinery.mas.bg.ac.rs/handle/123456789/2965 AB - Three-dimensional (3-D) shape modelling from a flat sheet by lasers needs numerous irradiations along surface paths with different parameters of heating. In this study it was attempted to form a three-dimensional shaped surface by laser. The main aim of the study was to analyse the impact of various machining parameters like laser power, scan speed and spot diameters on the surface modelling process. Adaptive neuro-fuzzy inference system (ANFIS) and variable selection procedure was used in order to determine the parameters influence on the surface heights prediction. The selection procedure was done to obtain the found the process parameters which has the highest influence on the surface heights. The method can produce results to simplify the surface heights prediction. PB - Old City Publishing T2 - Lasers in Engineering T1 - Analysis of the Laser Forming of Shaped Surfaces Using the Adaptive Neuro-fuzzy Technique EP - 340 IS - 4-6 SP - 333 VL - 40 UR - https://hdl.handle.net/21.15107/rcub_machinery_2965 ER -
@article{ author = "Jović, Srdjan and Skulić, A. and Lazarević, Mihailo", year = "2018", abstract = "Three-dimensional (3-D) shape modelling from a flat sheet by lasers needs numerous irradiations along surface paths with different parameters of heating. In this study it was attempted to form a three-dimensional shaped surface by laser. The main aim of the study was to analyse the impact of various machining parameters like laser power, scan speed and spot diameters on the surface modelling process. Adaptive neuro-fuzzy inference system (ANFIS) and variable selection procedure was used in order to determine the parameters influence on the surface heights prediction. The selection procedure was done to obtain the found the process parameters which has the highest influence on the surface heights. The method can produce results to simplify the surface heights prediction.", publisher = "Old City Publishing", journal = "Lasers in Engineering", title = "Analysis of the Laser Forming of Shaped Surfaces Using the Adaptive Neuro-fuzzy Technique", pages = "340-333", number = "4-6", volume = "40", url = "https://hdl.handle.net/21.15107/rcub_machinery_2965" }
Jović, S., Skulić, A.,& Lazarević, M.. (2018). Analysis of the Laser Forming of Shaped Surfaces Using the Adaptive Neuro-fuzzy Technique. in Lasers in Engineering Old City Publishing., 40(4-6), 333-340. https://hdl.handle.net/21.15107/rcub_machinery_2965
Jović S, Skulić A, Lazarević M. Analysis of the Laser Forming of Shaped Surfaces Using the Adaptive Neuro-fuzzy Technique. in Lasers in Engineering. 2018;40(4-6):333-340. https://hdl.handle.net/21.15107/rcub_machinery_2965 .
Jović, Srdjan, Skulić, A., Lazarević, Mihailo, "Analysis of the Laser Forming of Shaped Surfaces Using the Adaptive Neuro-fuzzy Technique" in Lasers in Engineering, 40, no. 4-6 (2018):333-340, https://hdl.handle.net/21.15107/rcub_machinery_2965 .