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| Research on the prediction and control method of laser melting morphology of high entropy alloy materials based on NSGA-II
algorithm |
| QUE Linzhi1，2，LIAN Guofu1，2，FENG Meiyan1，2，HUANG Xu1，2，LAN Ruqing1，2 |
| （1.School of Mechanical and Automotive Engineering, FuJian University of Technology, Fuzhou 350118, China;
2.Fujian Key Laboratory of Intelligent Machining Technology and Equipment, Fujian University of Technology,
Fuzhou 350118, China） |
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Abstract As a new type of material developed in metal materials in recent years, HEAs have large lattice distor‐
tion, high configuration entropy, high strength, good toughness, corrosion resistance, high-temperature oxidation re‐
sistance, and high temperature softening resistance. In terms of research on high-entropy alloy materials, the exist‐
ing research mainly focuses on the influences of laser cladding on the structure and properties of high-entropy alloy
coatings, rather than process parameters on the forming quality of high-entropy alloy coatings by laser cladding. Al‐
CoCrFeNiTi high-entropy alloy coatings were prepared on AISI 45 steel substrates by laser cladding in the work.
Aiming at the forming quality of laser cladding high-entropy alloy materials, the work explored the influences of
process parameters on the dilution rate, aspect ratio, and cladding area to predict and optimize the cladding quality.
The mathematical model of the process parameters, dilution rate, aspect ratio, and cladding area was established by
the response surface methodology (RSM) to analyze the influences of laser power, scanning speed, and powder
feeding voltage on the morphology of AlCoCrFeNiTi-coating cladding layer. The RSM can establish a mathemati‐
cal relationship model between input variables and output quantities. The work used the Box-Behnken design (BBD) module in the RSM，The model of the process parameters and the interaction relationship between the pa‐
rameters on the response value could be established by the BBD. Besides, multi-objective optimization is per‐
formed by the NSGA-Ⅱ genetic algorithm. After optimization, the process parameters are obtained as the laser pow‐
er of 1,770.60 W, a scanning speed of 5.96 mm/s, and a powder feeding voltage of 23.26 V. The actual value-error
ratios of the dilution rate, aspect ratio, and cladding area are verified by experiments to be 6.69, 9.27, and 11.96%,
respectively. The dilution rate increases with increased laser power and scanning speed and decreases with the
increased powder-feeding voltage. The aspect ratio decreases with the increased scanning speed and increased with
the increased powder-feeding voltage. With the change of laser power, the aspect ratio first decreased and then in‐
creased. The effect of laser power on the cladding area is not significant, and the cladding area decreases with the
increased scanning speed and increases with the increased powder-feeding voltage. The maximum microhardness
of the HEA clad layer processes with the optimized parameter set is 858.9HV, which is about four times that of the
base material (215.8 HV). The AlCoCrFeNiTi HEA clad layer consists of BCC phase and TiC phase, which is con‐
sistent with the formation of simple solid solution phase in the HEA clad layer. The HEA clad layer of the opti‐
mized parameter group has good metallurgical bonding with the substrate, the coating is dense and the grains are re‐
fined.The research results can provide a theoretical basis for the prediction and control of the morphology of highentropy alloy materials prepared by laser cladding.
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Received: 15 July 2022
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Corresponding Authors:
练国富（1980—），男，博士，教授，主要研究方向为激光增材制造、激光表面工程。
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2023, Vol. 33 
