光谱学与光谱分析, 2020, 40 (7): 2289, 网络出版: 2020-12-06  

基于激光诱导击穿光谱的增材制造成分梯度不锈钢样品的成分分布研究及应用

Study on the Element Distribution of Gradient Stainless Steel Samples Prepared by Additive Manufacturing and Its Application Based on Laser Induced Breakdown Spectroscopy
作者单位
1 钢铁研究总院, 北京 100081
2 金属材料表征北京市重点实验室, 北京 100081
3 钢研纳克检测技术股份有限公司, 北京 100081
摘要
增材制造由于加工速度快, 精度高, 无需模具成形常用于制备复杂的金属部件, 成分梯度样品的制备更是金属增材制造中的热门, 由于该技术目前尚未成熟, 工件中往往存在较多缺陷, 匹配的成分分布分析方法的研究对成品质量监测具有重要意义。 宏观的成分分布表征手段主要有激光诱导击穿光谱原位统计分析技术(LIBS-OPA)和火花源原子发射光谱原位统计分布分析技术(Spark-OPA)两种, Spark-OPA由于激发斑点较大不适用于增材制造样品的逐层分析, LIBS-OPA具有多元素同步定位分析、 空间分辨率高、 分析尺度较大、 样品损伤量小等诸多优势, 可以实现金属块体材料的高精度成分分布表征。 采用激光诱导击穿光谱法对增材制造成分梯度不锈钢样品的成分分布表征方法进行了研究。 通过对仪器参数和分析条件进行优化, 保证了分析的灵敏度以及信号的稳定性, 确定最佳的测试条件为: 激光灯电压1.32 kV, 调Q延时280 μs, 样品室氩气气压6 300 Pa, 光斑直径200 μm, 0次预剥蚀, 积分15次剥蚀, 并在该条件下绘制Cr 298.9 nm, Ni 218.5 nm, Mn 293.3 nm, Mo 203.8 nm, Si 212.4 nm, P 178.3 nm, C 193.1 nm, Co 384.5 nm等元素的工作曲线, 大部分元素判定系数超过0.99。 使用LIBS-OPA对不同的多路送粉增材制造工艺制备出的两块成分梯度不锈钢样品进行了面扫描, 得到样品沉积面上8种元素的成分分布信息, 分析结果同火花源原子发射光谱原位统计分布分析技术(Spark-OPA)具有良好的一致性, 其定量准确性也通过火花直读光谱仪进行了验证。 该研究实现了增材制造样品的逐层分析, 并通过成分分布结果对样品的制备工艺提供了指导, 同时也对两种工艺制造出的样品中重复出现沿打印方向的裂纹带的成因进行了分析, 该研究对于增材制造工艺的改进和完善具有指导意义。
Abstract
Additive manufacturing technology is often used to prepare complex metal parts due to its high processing speed, high precision, and there is no need for molding for shaping. The preparation of component gradient samples is more popular in the manufacture of metal additives, Since the technology is not yet mature. There are often many defects in the workpiece. It is very important for the quality monitoring of additive manufacturing products to make the study of component distribution characterization method, which is suitable for additive manufacturing samples. The macroscopic component distribution characterization methods are mainly composed of Laser-induced breakdown spectroscopy combined with original position statistical distribution analysis (LIBS-OPA) and Spark source atomic emission spectroscopy combined with original position statistical distribution analysis (Spark-OPA), due to the large excitation spot, Spark- OPA is not suitable for layer-by-layer analysis of additive manufacturing samples. LIBS-OPA has gradually been used to characterize the element distribution of metal block samples with the advantages of multi-element synchronous positioning analysis, high spatial resolution, large optional analysis area, small sample damage, This method can achieve high-precision composition distribution characterization of metal workpieces. In this paper, the composition distribution of gradient stainless steel samples prepared by additive manufacturing technology was studied by laser induced breakdown spectroscopy. By optimizing the instrument parameters and analysis conditions, the analytical sensitivity and signal stability was ensured. The optimum test conditions were selected as follows: laser lamp voltage 1.32 kV, Q-switching delay 280 μs, sample chamber argon pressure 6 300 Pa, spot diameter 200 μm, 0 pre-denudation, integration of 15 denudations. Under this condition, the calibration curves of Cr with spectrum line of 298.9 nm, Ni with spectrum line of 218.5 nm, Mo with spectrum line of 203.8 nm, Si with spectrum line of 212.4 nm, P with spectrum line of 178.3 nm, C with spectrum line of 193.1 nm, Co with spectrum line of 384.5 nm, and Mn with a spectrum line of 293.3 nm was plotted. Most element determination coefficients exceed 0.99, Two gradient stainless steel samples prepared with different multi-pass powder feeding processes were scanned by LIBS-OPA. The distribution information of eight elements in the deposition surface of the samples was obtained. The quantitative distribution results had good agreement with Spark-OPA, and the quantitative accuracy has been verified by spark direct reading spectrometer. The study achieved a layer-by-layer analysis of additive manufacturing samples and selected the sample preparation process by composition distribution results. At the same time, the causes of cracks in the samples were also discussed through the characterization results of composition distribution. This research can play a guiding role in the improvement and perfection of the manufacturing process.

刘宗鑫, 沈学静, 李冬玲, 赵雷. 基于激光诱导击穿光谱的增材制造成分梯度不锈钢样品的成分分布研究及应用[J]. 光谱学与光谱分析, 2020, 40(7): 2289. LIU Zong-xin, SHEN Xue-jing, LI Dong-ling, ZHAO Lei. Study on the Element Distribution of Gradient Stainless Steel Samples Prepared by Additive Manufacturing and Its Application Based on Laser Induced Breakdown Spectroscopy[J]. Spectroscopy and Spectral Analysis, 2020, 40(7): 2289.

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