激光熔化沉积TC4钛合金电涡流检测仿真及亚表面缺陷检测
Eddy Current Testing Simulation and Subsurface Defect Detection of TC4 Titanium Alloy for Laser Melting Deposition
赵宇辉 1赵吉宾 1李明玥 2何振丰 1王志国 1贺晨1
作者信息
- 1. 中国科学院沈阳自动化研究所 沈阳 110016;中国科学院机器人与智能制造创新研究院 沈阳 110169
- 2. 中国科学院沈阳自动化研究所 沈阳 110016;中国科学院机器人与智能制造创新研究院 沈阳 110169;沈阳工业大学材料科学与工程学院 沈阳 110870
- 折叠
摘要
激光熔化沉积零件制造及使用过程中容易产生缺陷,电涡流检测是一种非接触检测方法,针对表面及亚表面缺陷具有很高的检测灵敏度,易于实现自动化检测,在增材制造领域极具应用前景.通过有限元仿真技术建立无缺陷TC4钛合金增材样件电涡流检测模型,模拟电涡流检测过程中电场强度的分布规律,研究激励频率、提离量对电涡流检测信号的影响.研究发现,针对样件内不同深度的位置激励频率存在最佳区间,而提离量则应尽可能采用较小值.采用激光熔化沉积技术制备了含有亚表面缺陷的TC4钛合金试验样件,用于电涡流检测试验测试,将电涡流检测设备与机器人集成,采用机器人做执行机构来保证提离量及运动的平稳性,最终获得的试验结果与仿真结果具有较好的一致性.
Abstract
Parts produced by laser melting deposition are prone to defects during the manufacturing and service.Eddy current testing is a non-contact testing method,which has high detection sensitivity for surface and sub-surface defects and is easy for automatic detection,so it has a great application prospect in the field of additive manufacturing.A defect-free additive manufacturing model of TC4 titanium alloy was established for eddy current testing by finite element simulation technology,and the distribution of electric field intensity during eddy current testing was simulated,and then,the influence of excitation frequency and lift-off distance on eddy current testing signal is studied.It was found that there is an optimal range for the excitation frequency at different depths in the sample,and the lift-off distance adopted should be as small as possible.Then a TC4 titanium alloy sample with subsurface defects were prepared by laser melting deposition technology for eddy current testing experiments.The eddy current testing equipment was integrated with a robot,and the robot was used as the actuator to ensure the lift-off distance and the movement stability.Finally the test results were in good agreement with the simulation results.
关键词
激光熔化沉积/电涡流检测/有限元仿真/TC4钛合金/亚表面缺陷Key words
laser melting deposition/eddy current testing/finite element simulation/TC4 titanium alloy/subsurface defects引用本文复制引用
基金项目
国家自然科学基金(52105415)
国防科技重点实验室基金(JCKY61420052017)
广东省基础与应用基础研究基金(2020B1515120027)
出版年
2024
NETL
NSTL
万方数据