Laser surface transformation hardening becomes one of the most modern processes used to improve fatigue and wear properties of steel surfaces. In this process, the material properties and the heating parameters are th...Laser surface transformation hardening becomes one of the most modern processes used to improve fatigue and wear properties of steel surfaces. In this process, the material properties and the heating parameters are the factors that present the most significant effects on the hardened surface attributes. The control of these factors using predictive modeling approaches to achieve desired surface properties leads to conclusive results. However, when the dimensions of the surface to be treated are larger than the cross-section of the laser beam, various laser-scanning patterns are involved. This paper presents an experimental investigation of laser surface hardening of AISI 4340 steel using different laser scanning patterns. This investigation is based on a structured experimental design using the Taguchi method and improved statistical analysis tools. Experiments are carried out using a 3 kW Nd: YAG laser source in order to evaluate the effects of the heating parameters and patterns design parameters on the physical and geometrical characteristics of the hardened surface. Laser power, scanning speed and scanning patterns (linear, sinusoidal, triangular and trochoid) are the factors used to evaluate the hardened depth and the hardened width variations and to identify the possible relationship between these factors and the hardened zone attributes. Various statistical tools such as ANOVA, correlations analysis and response surfaces are applied in order to examine the effects of the experimental factors on the hardened surface characteristics. The results reveal that the scanning patterns do not modify the nature of the laser parameters’ effects on the hardened depth and the hardened width. But they can accentuate or reduce these effects depending on the type of the considered pattern. The results show also that the sinusoidal and the triangular patterns are relevant when a maximum hardened width with an acceptable hardened depth is desired.展开更多
Quality assessment and prediction becomes one of the most critical requirements for improving reliability, efficiency and safety of laser surface transformation hardening process (LSTHP). Accurate and efficient model ...Quality assessment and prediction becomes one of the most critical requirements for improving reliability, efficiency and safety of laser surface transformation hardening process (LSTHP). Accurate and efficient model to perform non-destructive quality estimation is an essential part of the assessment. This paper presents a structured and comprehensive approach developed to design an effective artificial neural network (ANN) based model for quality estimation and prediction in LSTHP using a commercial 3 kW Nd:Yag laser. The proposed approach examines laser hardening parameters and conditions known to have an influence on performance characteristics of hardened surface such as hardened bead width (HBW) and hardened depth (HD) and builds a quality prediction model step by step. The modeling procedure begins by examining, through a structured experimental investigations and exhaustive 3D finite element method simulation efforts, the relationships between laser hardening parameters and characteristics of hardened surface and their sensitivity to the process conditions. Using these results and various statistical tools, different quality prediction models are developed and evaluated. The results demonstrate that the ANN based assessment and prediction proposed approach can effectively lead to a consistent model able to accurately and reliably provide an appropriate prediction of hardened surface characteristics under variable hardening parameters and conditions.展开更多
通过电弧炉留钢操作,控制EAF终点[C]≥0.10%,LF精炼白渣时间≥30 min,利用淬透性预测模型微调钢水中元素含量,控制中间包钢水过热度15~30℃、结晶器、铸流和末端电磁搅拌等工艺措施,试制的φ110mm~φ150 mm 22CrMoH齿轮钢(/%:0.20~0.22C...通过电弧炉留钢操作,控制EAF终点[C]≥0.10%,LF精炼白渣时间≥30 min,利用淬透性预测模型微调钢水中元素含量,控制中间包钢水过热度15~30℃、结晶器、铸流和末端电磁搅拌等工艺措施,试制的φ110mm~φ150 mm 22CrMoH齿轮钢(/%:0.20~0.22C,0.26~0.28Si,0.73~0.75Mn,0.007~0.012P,0.001~0.004S,1.05~1.09Cr,0.37~0.39Mo)的氧含量为8×10^(-6)~10×10^(-6),轧材J_(15)△HRC值≤4,夹杂物≤1.0级,低倍组织≤1.0级。展开更多
文摘Laser surface transformation hardening becomes one of the most modern processes used to improve fatigue and wear properties of steel surfaces. In this process, the material properties and the heating parameters are the factors that present the most significant effects on the hardened surface attributes. The control of these factors using predictive modeling approaches to achieve desired surface properties leads to conclusive results. However, when the dimensions of the surface to be treated are larger than the cross-section of the laser beam, various laser-scanning patterns are involved. This paper presents an experimental investigation of laser surface hardening of AISI 4340 steel using different laser scanning patterns. This investigation is based on a structured experimental design using the Taguchi method and improved statistical analysis tools. Experiments are carried out using a 3 kW Nd: YAG laser source in order to evaluate the effects of the heating parameters and patterns design parameters on the physical and geometrical characteristics of the hardened surface. Laser power, scanning speed and scanning patterns (linear, sinusoidal, triangular and trochoid) are the factors used to evaluate the hardened depth and the hardened width variations and to identify the possible relationship between these factors and the hardened zone attributes. Various statistical tools such as ANOVA, correlations analysis and response surfaces are applied in order to examine the effects of the experimental factors on the hardened surface characteristics. The results reveal that the scanning patterns do not modify the nature of the laser parameters’ effects on the hardened depth and the hardened width. But they can accentuate or reduce these effects depending on the type of the considered pattern. The results show also that the sinusoidal and the triangular patterns are relevant when a maximum hardened width with an acceptable hardened depth is desired.
文摘Quality assessment and prediction becomes one of the most critical requirements for improving reliability, efficiency and safety of laser surface transformation hardening process (LSTHP). Accurate and efficient model to perform non-destructive quality estimation is an essential part of the assessment. This paper presents a structured and comprehensive approach developed to design an effective artificial neural network (ANN) based model for quality estimation and prediction in LSTHP using a commercial 3 kW Nd:Yag laser. The proposed approach examines laser hardening parameters and conditions known to have an influence on performance characteristics of hardened surface such as hardened bead width (HBW) and hardened depth (HD) and builds a quality prediction model step by step. The modeling procedure begins by examining, through a structured experimental investigations and exhaustive 3D finite element method simulation efforts, the relationships between laser hardening parameters and characteristics of hardened surface and their sensitivity to the process conditions. Using these results and various statistical tools, different quality prediction models are developed and evaluated. The results demonstrate that the ANN based assessment and prediction proposed approach can effectively lead to a consistent model able to accurately and reliably provide an appropriate prediction of hardened surface characteristics under variable hardening parameters and conditions.
文摘通过电弧炉留钢操作,控制EAF终点[C]≥0.10%,LF精炼白渣时间≥30 min,利用淬透性预测模型微调钢水中元素含量,控制中间包钢水过热度15~30℃、结晶器、铸流和末端电磁搅拌等工艺措施,试制的φ110mm~φ150 mm 22CrMoH齿轮钢(/%:0.20~0.22C,0.26~0.28Si,0.73~0.75Mn,0.007~0.012P,0.001~0.004S,1.05~1.09Cr,0.37~0.39Mo)的氧含量为8×10^(-6)~10×10^(-6),轧材J_(15)△HRC值≤4,夹杂物≤1.0级,低倍组织≤1.0级。
