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High-speed laser cladding shows significant potential for application in the field of high-performance surface hardening due to its low heat input and high cladding efficiency. However, the pool solidification time is significantly reduced at high scanning speeds, resulting in a narrower process window and making it more difficult to ensure coating formation stability and control performance. Therefore, this study employed high-speed laser cladding technology to prepare FeCrNiB alloy coatings, and systematically conducted research on process parameter optimization and friction properties. Firstly, the response surface method (RSM) was used to establish quantitative relationship models between laser power, scanning speed, and powder feed rate and the dilution ratio, forming coefficient, and microhardness. Then, the hybrid differential evolution and NSGA-II algorithm (DE-NSGA-II) was employed for multi-objective optimization. Finally, a systematic analysis was conducted on the friction and wear properties of the coatings produced under the optimal process parameters. The results indicate that the interaction between laser power and scanning speed has a significant impact on the dilution behavior of the coating, while the coupling between scanning speed and powder feed rate governs the formation characteristics and microhardness evolution of the coating. The experiment verified that the prediction error for the optimal parameters is controlled within 5%, demonstrating good engineering applicability. Further analysis indicates that grain refinement and the formation of strengthening phases in the optimal coating are the key mechanisms behind the significant improvement in hardness and wear resistance, and the coating primarily exhibits a mild abrasive wear mechanism. This work realizes the multi-objective optimization of the high-speed laser cladding process via RSM and DE-NSGA-II algorithm, which provides a novel and efficient method for parameter optimization and engineering application of high-speed laser cladding.
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Weiyuan Guo
Huanghe Science and Technology College
Anjun Li
Huanghe Science and Technology College
Yanyan Wang
Shaanxi University of Technology
Coatings
Shaanxi University of Technology
Huanghe Science and Technology College
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Guo et al. (Mon,) studied this question.
synapsesocial.com/papers/6a0fb75992676d5461fd00a0 — DOI: https://doi.org/10.3390/coatings16050581
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