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基于正交试验设计的45钢激光表面强化工艺优化
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  • 英文篇名:Optimization of Laser Surface Strengthening Technology for 45 Steel Based on Orthogonal Test Design
  • 作者:张伟 ; 刘政 ; 周刘勇 ; 赵海生
  • 英文作者:ZHANG Wei;LIU Zheng;ZHOU Liuyong;ZHAO Haisheng;School of Mechanical and Electrical Engineering,Jiangxi University of Science and Technology;
  • 关键词:激光表面强化 ; 正交试验设计 ; 工艺优化 ; 磨损率
  • 英文关键词:laser surface hardening;;orthogonal experimental design;;process optimization;;wear rate
  • 中文刊名:RHMF
  • 英文刊名:Lubrication Engineering
  • 机构:江西理工大学机电工程学院;
  • 出版日期:2019-02-15
  • 出版单位:润滑与密封
  • 年:2019
  • 期:v.44;No.330
  • 基金:国家自然科学基金项目(50801032);; 江西省自然科学基金项目(2008GQC0027)
  • 语种:中文;
  • 页:RHMF201902017
  • 页数:6
  • CN:02
  • ISSN:44-1260/TH
  • 分类号:91-96
摘要
利用激光表面重熔强化技术对45钢表面进行重熔处理,以显微硬度和磨损率为考察指标,采用正交试验方法考察激光功率、扫描速度、光斑直径和脉宽4个参数对45钢表面综合性能的影响。结果表明:4个参数对45钢表面综合性能的影响作用由主到次的顺序依次为激光功率、光斑直径、扫描速度、脉宽;最优的激光表面强化工艺参数为激光功率650 W,扫描速度100 mm/min,光斑直径4 mm,脉宽2.4 ms。利用硬度测试仪和摩擦磨损试验机,对采用最优的激光表面强化工艺参数制备的试样的显微硬度和磨损率进行测试,结果表明:采用优化参数制备的试样的激光强化层硬度值分布较为均匀,且硬度值也较高,且与优化前试样相比磨损率明显降低;优化前试样磨损机制为疲劳磨损、磨粒磨损、黏着磨损,优化后试样磨损表面仅有一些微小的划痕,耐磨性能明显改善。
        The surface of 45 steel was remelted by using laser surface remelting strengthening technology.With microhardness and wear rate as indicators,the indluence of laser power,scanning speed,beam diameter and pulse width on the comprehensive properties of 45 steel was investigated.It is found that laser power has the greatest influence on the comprehensive properties of 45 steel surface,followed by spot diameter,scanning velocity,laser pulse width.The optimum laser surface hardening parameters are 650 W of laser power,100 mm/min of scanning speed,4 mm of spot diameter and 2.4 ms of pulse width.The micro hardness and wear rate of the samples prepared by optimum laser surface hardening parameters were tested by hardness tester and friction and wear tester.The results show that the hardness distribution of laser hardening layer prepared with optimized parameters is more uniform and the hardness value is higher,the wear rate is obviously lower than that of the sample before parameter optimization.The wear mechanism of the samples before parameter optimization is fatigue wear,abrasive wear and adhesion wear.After optimization,there are only some small scratches on the wear surface of the samples,and the wear resistance is obviously improved.
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