Case depth measurement of the induction hardened steel parts is necessary for quality control. Vickers microhardness test is the most industrially accepted method to identify the case depth. But this method is a time ...Case depth measurement of the induction hardened steel parts is necessary for quality control. Vickers microhardness test is the most industrially accepted method to identify the case depth. But this method is a time consuming one and it requires expensive equipment. The aim of this study is to develop a different method to determine the case depth using image processing. The surface hardened steel samples were cross cut, ground and etched with Nital. The etched macrosectioned specimens were scanned by a scanner. The scanned images were evaluated by the developed software. The principle of the software is to identify the gray level difference. The effective case depths of the surface hardened specimens obtained by Vickers microhardness test and the developed method were compared. It was found that the deviation of the developed method was ±0.12 mm at the case depth range of 0.6 - 2.0 mm and mm at the case depth range of 2.1 - 4.3 mm. The measuring time was only 20% of Vickers microhardness test. The deviation range is much lower than the tolerance case depth specification for induction hardening in general.展开更多
Induction hardening of dense Fe–Cr/Mo alloys processed via the powder-metallurgy route was studied. The Fe-3Cr-0.5Mo, Fe-1.5Cr-0.2Mo, and Fe-0.85 Mo pre-alloyed powders were mixed with 0.4wt%, 0.6wt%, and 0.8wt% C an...Induction hardening of dense Fe–Cr/Mo alloys processed via the powder-metallurgy route was studied. The Fe-3Cr-0.5Mo, Fe-1.5Cr-0.2Mo, and Fe-0.85 Mo pre-alloyed powders were mixed with 0.4wt%, 0.6wt%, and 0.8wt% C and compacted at 500, 600, and 700 MPa, respectively. The compacts were sintered at 1473 K for 1 h and then cooled at 6 K/min. Ferrite with pearlite was mostly observed in the sintered alloys with 0.4wt% C, whereas a carbide network was also present in the alloys with 0.8wt% C. Graphite at prior particle boundaries led to deterioration of the mechanical properties of alloys with 0.8wt% C, whereas no significant induction hardening was achieved in alloys with 0.4wt% C. Among the investigated samples, alloys with 0.6wt% C exhibited the highest strength and ductility and were found to be suitable for induction hardening. The hardening was carried out at a frequency of 2.0 kHz for 2–3 s. A case depth of 2.5 mm was achieved while maintaining the bulk(interior) hardness of approximately HV 230. A martensitic structure was observed on the outer periphery of the samples. The hardness varied from HV 600 to HV 375 from the sample surface to the interior of the case hardened region. The best combination of properties and hardening depth was achieved in case of the Fe-1.5Cr-0.2Mo alloy with 0.6wt% C.展开更多
This paper presents a numerical and experimental analysis study of the temperature distribution in a cylindrical specimen heat treated by laser and quenched in ambient temperature. The cylinder studied is made of AISI...This paper presents a numerical and experimental analysis study of the temperature distribution in a cylindrical specimen heat treated by laser and quenched in ambient temperature. The cylinder studied is made of AISI-4340 steel and has a diameter of 14.5-mm and a length of 50-mm. The temperature distribution is discretized by using a three-dimensional numerical finite difference method. The temperature gradient of the transformation of the microstructure is generated by a laser source Nd-YAG 3.0-kW manipulated using a robotic arm programmed to control the movements of the laser source in space and in time. The experimental measurement of surface temperature and air temperature in the vicinity of the specimen allows us to determine the values of the absorption coefficient and the coefficient of heat transfer by convection, which are essential data for a precise numerical prediction of the case depth. Despite an unsteady dynamic regime at the level of convective and radiation heat losses, the analysis of the averaged results of the temperature sensors shows a consistency with the results of microhardness measurements. The feasibility and effectiveness of the proposed approach lead to an accurate and reliable mathematical model able to predict the temperature distribution in a cylindrical workpiece heat treated by laser.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
文摘Case depth measurement of the induction hardened steel parts is necessary for quality control. Vickers microhardness test is the most industrially accepted method to identify the case depth. But this method is a time consuming one and it requires expensive equipment. The aim of this study is to develop a different method to determine the case depth using image processing. The surface hardened steel samples were cross cut, ground and etched with Nital. The etched macrosectioned specimens were scanned by a scanner. The scanned images were evaluated by the developed software. The principle of the software is to identify the gray level difference. The effective case depths of the surface hardened specimens obtained by Vickers microhardness test and the developed method were compared. It was found that the deviation of the developed method was ±0.12 mm at the case depth range of 0.6 - 2.0 mm and mm at the case depth range of 2.1 - 4.3 mm. The measuring time was only 20% of Vickers microhardness test. The deviation range is much lower than the tolerance case depth specification for induction hardening in general.
基金the support of the MHRD fellowship from Government of India
文摘Induction hardening of dense Fe–Cr/Mo alloys processed via the powder-metallurgy route was studied. The Fe-3Cr-0.5Mo, Fe-1.5Cr-0.2Mo, and Fe-0.85 Mo pre-alloyed powders were mixed with 0.4wt%, 0.6wt%, and 0.8wt% C and compacted at 500, 600, and 700 MPa, respectively. The compacts were sintered at 1473 K for 1 h and then cooled at 6 K/min. Ferrite with pearlite was mostly observed in the sintered alloys with 0.4wt% C, whereas a carbide network was also present in the alloys with 0.8wt% C. Graphite at prior particle boundaries led to deterioration of the mechanical properties of alloys with 0.8wt% C, whereas no significant induction hardening was achieved in alloys with 0.4wt% C. Among the investigated samples, alloys with 0.6wt% C exhibited the highest strength and ductility and were found to be suitable for induction hardening. The hardening was carried out at a frequency of 2.0 kHz for 2–3 s. A case depth of 2.5 mm was achieved while maintaining the bulk(interior) hardness of approximately HV 230. A martensitic structure was observed on the outer periphery of the samples. The hardness varied from HV 600 to HV 375 from the sample surface to the interior of the case hardened region. The best combination of properties and hardening depth was achieved in case of the Fe-1.5Cr-0.2Mo alloy with 0.6wt% C.
文摘This paper presents a numerical and experimental analysis study of the temperature distribution in a cylindrical specimen heat treated by laser and quenched in ambient temperature. The cylinder studied is made of AISI-4340 steel and has a diameter of 14.5-mm and a length of 50-mm. The temperature distribution is discretized by using a three-dimensional numerical finite difference method. The temperature gradient of the transformation of the microstructure is generated by a laser source Nd-YAG 3.0-kW manipulated using a robotic arm programmed to control the movements of the laser source in space and in time. The experimental measurement of surface temperature and air temperature in the vicinity of the specimen allows us to determine the values of the absorption coefficient and the coefficient of heat transfer by convection, which are essential data for a precise numerical prediction of the case depth. Despite an unsteady dynamic regime at the level of convective and radiation heat losses, the analysis of the averaged results of the temperature sensors shows a consistency with the results of microhardness measurements. The feasibility and effectiveness of the proposed approach lead to an accurate and reliable mathematical model able to predict the temperature distribution in a cylindrical workpiece heat treated by laser.
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.
