文献类型：期刊文献

英文题名：Parameters Optimization of the Laser Cladding of a Fe-based VC Composite Coating Using Response Surface Methodology (RSM)

作者：Liang, Z-G[1];Zhan, J-M[1];Shi, W-Q[1];Xie, Y-P[1];Huang, J.[1];An, F-J[2];Lai, X-H[1]

机构：[1]Guangdong Ocean Univ, Coll Elect & Informat Engn, Zhanjiang 524088, Guangdong, Peoples R China;[2]Guangdong Ocean Univ, Coll Mech & Power Engn, Zhanjiang 524088, Guangdong, Peoples R China

年份：2021

卷号：49

期号：4-6

起止页码：179

外文期刊名：LASERS IN ENGINEERING

收录：SCI-EXPANDED(收录号：WOS:000629987600001)、、EI(收录号：20213210724107)、Scopus(收录号：2-s2.0-85111759281)、WOS

基金：This study was supported by the Natural Science Foundation of Guangdong Province, China (Grant No. 2015A030310354), the Zhanjiang Municipal Science and Technology Program (Project No. 2019A01035), the University Innovation Program of Guangdong Ocean University (Project No. GDOU2017052504) and the Characteristic Innovation Program for Colleges and Universities in Guangdong Province, China (Project Nos. Q18267, Q19012 and 230419105).

语种：英文

外文关键词：Nd:YAG laser; iron; Fe; vanadium; V; Carbon; C; T9A tool steel; Fe-based coating; laser cladding; parameter optimization; response surface methodology (RSM); dilution rate; width-to-height ratio

外文摘要：In order to acquire good Fe-based VC composite coating by laser cladding and minimize cracks and pores during preparation, we designed an experimental scheme with response surface methodology (RSM) and studied effects of laser process parameters, such as output current, pulse width, pulse frequency, and scanning speed, on geometric characteristics and quality of the clad coating. A mathematical model was established for clad geometric features and dilution rate. Analysis of variance of test results shows that, the greater the pulse width, the greater the clad dilution rate; synergy of large output current and low scanning speed will give rise to greater clad width-to-height ratio. Through analysis and discussion, a set of optimum laser process parameters were obtained, and based on verification test, the errors between predicted value and measured value for the optimum process parameters were small, indicating high confidence level of this regression prediction model.