Laser Technology, Volume. 48, Issue 5, 759(2024)

Optimization of process parameters for laser cladding 316L on gray iron surface based on GA

BI Shaoping1, WANG Sheng1、*, ZHANG Enming1, CHEN Cong2, and CHEN Xiguo1
Author Affiliations
  • 1Mechanical and Electrical Engineering College, Quzhou College of Technology, Quzhou 324000, China
  • 2Zhejiang Heco Intelligent Equipment Co. Ltd., Quzhou 324000, China
  • show less

    In order to improve the comprehensive performance of HT250 gray cast iron material, a genetic algorithm(GA) multi-objective process parameter optimization method was used to obtain the corresponding empirical parameter group. In the laser cladding 316L alloy experiment on the surface of gray cast iron material, a digital detection instrument was used to comprehensively analyze the changes in macroscopic morphology, Rockwell hardness, geometric shape, and other characteristics of the sample, and the optimal process parameter combination was analyzed and optimized. The results show that when the process parameters are respectively set to powder feeding speed of 0.25 g/s, scanning speed of 10 mm/s, and laser power of 2800 W, the surface geometry of the 316L cladding layer is the best, the macroscopic morphology is good, and the maximum Rockwell hardness reaches 37.6 HRC. The sample cladding performance is good. The comprehensive improvement of various properties of gray cast iron provides practical reference for the repair and reuse of worn gray cast iron products.

    Tools

    Get Citation

    Copy Citation Text

    BI Shaoping, WANG Sheng, ZHANG Enming, CHEN Cong, CHEN Xiguo. Optimization of process parameters for laser cladding 316L on gray iron surface based on GA[J]. Laser Technology, 2024, 48(5): 759

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category:

    Received: Sep. 11, 2023

    Accepted: Dec. 2, 2024

    Published Online: Dec. 2, 2024

    The Author Email: WANG Sheng (158942287@qq.com)

    DOI:10.7510/jgjs.issn.1001-3806.2024.05.022

    Topics