Abstract
To improve the cladding quality of Ni-based powder on gray cast iron by high-speed laser cladding, ANSYS was used to construct the cladding model. The effects of laser power P, scanning rate v, and spot diameter r on the cladding quality were explored in terms of substrate surface temperature, temperature gradient G/solidification rate R, and heat-affected zone (HAZ) by the three-factor and three-level orthogonal test. The parameters that significantly affect the factors v and r were determined. Based on simulation tests, the effect of P on the microstructure, hardness and wear resistance of the molten layer was investigated by using scanning electron microscopy (SEM), hardness tester, friction wear machine and ultra-depth of field. The results showed that the microstructure of the cladding layer became sparse and coarse with increasing P, and the cross-sectional hardness and surface hardness didn’t change much. Compared to 2000 W, the wear quality loss of 1600 and 2400 W is improved by 24.8, 40.4%. The best wear resistance was achieved for 2000 W. The wear resistance and bond strength of Ni-based coating are optimal when v = 3 mm, r = 30 mm/s, and P = 2000 W.
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Data Availability
The datasets generated during and/or analyzed during the current study are available from the corresponding authors upon reasonable request.
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Funding
This research was supported financially by the National Natural Science Foundation of China (No. 52275358) and University Doctoral Research Initiation Grant (No. 2023085).
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All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by RW, MM, CO, RW and CZ. The first draft of the manuscript was written by HL and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
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Li, H., Mao, M., Wang, R. et al. Numerical Optimization and Performance Study of Ni-Based Coatings on Gray Cast Iron Surface by High-Speed Laser Cladding Based on Orthogonal Test. J. of Materi Eng and Perform (2024). https://doi.org/10.1007/s11665-024-09487-3
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DOI: https://doi.org/10.1007/s11665-024-09487-3