Abstract
The dilution rate has a significant impact on the composition and microstructure of the coatings, and the dilution rate and process parameters have a complex coupling relationship. In this study, three process parameters, namely laser power, powder feeding rate, and scanning speed, were selected as variables to design the orthogonal experiment. The dilution rate and hardness data were obtained from AlCoCrFeNi coatings based on orthogonal experiments. Then, a BP neural network was used to establish a prediction model of the process parameters on the dilution rate. The established BP neural network exhibited good prediction of the dilution rate of AlCoCrFeNi coatings, and the average relative error between the predicted value and the experimental value was only 5.89%. Subsequently, the AlCoCrFeNi coating was fabricated with the optimal process parameters. The results show that the coating was well-formed without defects, such as cracks and pores. The microhardness of the AlCoCrFeNi coating prepared with the optimal process parameters was 521.6 HV0.3. The elements were uniformly distributed in the microstructure, and the grain size was about 20–60 μm. The microstructure of the AlCoCrFeNi coating was only composed of the BCC phase without the existence of the FCC phase and intermetallic compounds.
Highlights
Laser cladding is an important surface modification technology that uses a highenergy laser beam to melt and deposit powder or wire on a substrate surface to form a single-layer or multi-layer coating
The AlCoCrFeNi alloy is a typical high-entropy alloy with an equal atomic ratio, and it possesses excellent mechanical properties, because its microstructure is mainly composed of the BCC phase [9]
Guo et al [21] used a BP neural network to optimize and predict the process parameters of laser cladding a Co-based alloy, and the average relative error between the predicted value and the experimental value was less than 10%
Summary
Laser cladding is an important surface modification technology that uses a highenergy laser beam to melt and deposit powder or wire on a substrate surface to form a single-layer or multi-layer coating. At a high dilution rate, a large amount of molten substrate enters into the AlCoCrFeNi coating, resulting in a sharp decrease of hardness. The elements from the molten substrate have an important influence on the microstructure of the AlCoCrFeNi high-entropy alloy coatings. It is of great significance to predict and control the dilution rate of the AlCoCrFeNi high-entropy alloy coating. Guo et al [21] used a BP neural network to optimize and predict the process parameters of laser cladding a Co-based alloy, and the average relative error between the predicted value and the experimental value was less than 10%. The effects of laser power, powder feeding rate, and scanning speed on the dilution rate of AlCoCrFeNi high-entropy alloy coatings were analyzed preliminarily.
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