激光诱导击穿光谱技术识别航空合金牌号

激光诱导击穿光谱(LIBS)作为一种多元素、高灵敏、非接触式的光谱分析技术,已经被广泛用于钢铁、铝合金等金属材料的定量与定性分析。为将LIBS技术用于航空合金牌号的高准确率识别,对6种不同牌号的航空合金进行了实验测量与分析。实验使用1 064nm的Nd∶YAG固体激光器作为激发源,采集了每种合金的100组光谱,每组光谱为100次激光脉冲的平均结果。将得到的航空合金光谱按7∶3的比例划分为训练集和测试集,分别利用全光谱数据和特征谱线数据建立偏最小二乘判别分析(PLS-DA)模型进行航空合金LIBS识别。两种模型得到训练集和测试集的识别正确率均为100%。研究结果表明,LIBS技术与化学计量学结合可以快速准确识别航空合金牌号,且基于特征谱线数据的PLS-DA模型在较少数据输入的情况下可取得与全光谱数据模型相同的结果。实验可为进一步开展航空合金LIBS现场检测工作提供方法参考。     

Quantitative analysis of C,Si, Mn,Ni, Cr and Cu in low-alloy steel under ambient conditions via laser-induced breakdown spectroscopy

A diode-pumped solid-state laser(DPSSL) with a high energetic stability and long service life is applied to ablate the steel samples instead of traditional Nd:YAG laser pumped by a xenon lamp,and several factors, such as laser pulse energy, repetition rate and argon flow rate, that influence laser-induced breakdown spectroscopy(LIBS) analytical performance are investigated in detail.Under the optimal experiment conditions, the relative standard deviations for C, Si, Mn, Ni, Cr and Cu are 3.3%–8.9%, 0.9%–2.8%, 1.2%–4.1%, 1.7%–3.0%, 1.1%–3.4% and 2.5%–8.5%,respectively, with the corresponding relative errors of 1.1%–7.9%, 1.0%–6.3%, 0.4%–3.9%,1.5%–6.3%, 1.2%–4.0% and 1.2%–6.4%. Compared with the results of the traditional spark discharge optical emission spectrometry technique, the analytical performance of LIBS is just a little inferior due to the less stable laser-induced plasma and smaller amount of ablated sample by the laser. However, the precision, detection limits and accuracy of LIBS obtained in our present work were sufficient to meet the requirements for process analysis. These technical performances of higher stability of output energy and longer service life for DPSSL, in comparison to the Q-switch laser pumped by xeon lamp, qualify it well for the real time online analysis for different industrial applications.     

Experimental investigation of combustion characteristics and NOx formation of coal particles using laser induced breakdown spectroscopy

To study the mechanism of coal combustion and NO_x formation, the combustion of coal particles in different atmospheres (O₂/N₂, O₂/CO₂) with different O₂ concentrations was investigated using the CO₂ laser as a heat source. The spatial distribution of atoms and groups (e.g., H at 656.2 nm, O at 777.3 nm, CN at 388.3 nm) relating to the combustion flame were measured simultaneously using laser induced breakdown spectroscopy (LIBS). The residual energy was measured during the collection of LIBS spectra in the combustion process, which could be characterized the temperature profiles of combustion flame due to the positive correlation with temperature. The combustion stage could be clearly discriminated by the emission of H and CN, along with the flame temperature. The residual energy obtained in different atmospheres indicated that the impact of combustion atmosphere on flame temperature is greater in the char combustion stage rather than volatile combustion stage. It was determined from the temporal and spatial distribution of residual energy and CN intensity that a higher flame temperature leads to a higher concentration of CN. The correlation between the generation of CN and the NO_x formation was also investigated to show that the formation approaches of NO_x are similar in the O₂/CO₂ and O₂/N₂ atmospheres, while the fuel-N conversion paths are different between volatile combustion and char combustion stages. The measurement of temporal and spatial distributions of LIBS spectra with varying flame temperatures is significant in revealing the mechanism of coal-particle combustion and NO_x formation.     

Spatio-temporal evaluation of Zr plasma parameters in a single-beam-splitting double-pulse laser-induced plasma

The plasma shielding effect is one of the major weaknesses of laser-induced breakdown spectroscopy(LIBS) as it causes non-linearity in signal strength. Although LIBS is typically carried out in constant laser energy, this non-linearity causes a reduction in sensitivity. In this work, we systematically examine laser-induced plasma, formed by two different excitation source modes, i.e. single pulse(SP)-excitation and single-beam-splitting double-pulse(SBSDP)-excitation over Zr-2.5% Nb alloy. The two most important plasma parameters influencing the emission line intensity, plasma temperature(T_e) and electron density(N_e) were studied and compared for both modes of laser excitation. Comparison of the results conclusively demonstrates that due to the splitting of the laser energy in the SBS-DP mode, the plasma shielding effect is significantly reduced. The reduced plasma shielding translates to an increased laser–sample coupling under SBS-DP mode. Temporal imaging of the total intensity of the laserinduced plasma in both excitation modes was also studied. The study shows how the plasma shielding effect can be reduced to improve the analytical quality of the LIBS methodology.     

自动聚焦在激光诱导击穿光谱检测中的应用

本文将自动聚焦方法应用于激光诱导击穿光谱(LIBS)检测技术中,利用自动聚焦方法控制激光在样品表面的聚焦位置和焦斑大小,以克服激光诱导击穿光谱系统检测样品时光谱强度的起伏变化较大的缺点,提高LIBS系统重复测量的精密度。并采用灰度差分法评价函数和改进后的爬山法成功实现了激光诱导击穿光谱技术检测中焦点位置的自动搜寻和调节,为LIBS检测仪开发了一套自动聚焦系统和相应的软硬件,较好地减小了LIBS光谱强度多次重复测量的相对标准偏差。     

激光诱导击穿光谱及其在元素分析中的应用

激光诱导击穿光谱是一种新的元素分析方法,但仍处于不断完善之中。利用它可以分析不同形态样品的成分,因此在成分分析和微量元素检测方面具有重要的应用前景。本文阐述了激光击穿诱导光谱仪的基本原理和激光诱导击穿光谱在多个领域中的应用,研究内容涉及固体样品、液体样品、气体样品、微量杂质分析和成分深度剖析等,并分析了基体效应、自吸收效应、测量时间、环境气体、激光参数等对激光诱导击穿光谱分析结果的影响。     

Quantitative analysis and time-resolved characterization of simulated tokamak exhaust gas by laser-induced breakdown spectroscopy

Tokamak exhaust is an important part of the deuterium-tritium fuel cycle system in fusion reactions. In this work, we present a laser-induced breakdown spectroscopy (LIBS)-based method to monitor the gas compositions from the exhaust system in the tokamak device. Helium (He), a main impurity in the exhaust gas, was mixed with hydrogen (H2) in different ratios through a self-designed gas distribution system, and sealed into a measurement chamber as a standard specimen. A 532 nm wavelength laser pulse with an output power of 100 mJ was used for plasma excitation. The time-resolved LIBS is used to study the time evolution characteristics of the signal strength, signal-to-background ratio (SBR), signal-to-noise ratio (SNR) and relative standard deviation (RSD) of the helium and hydrogen characteristic lines. The Boltzmann two-line method was employed to estimate the plasma temperature of laser-induced plasma (LIP). The Stark-broadened profile of He I 587.56 nm was exploited to measure the electron density. From these studies, an appropriate time was determined in which the low RSD% was consistent with the high signal-to-noise ratio. The He I 587.56 nm and Hα emission lines with good signal-to-noise ratio were extracted from the spectrum and used in the external standard method and internal standard method for quantitative analysis. The test results for mixed gas showed that the average relative error of prediction was less than 11.15%, demonstrating the great potential of LIBS in detecting impurities in plasma exhaust gas.     

不同离焦量延时时间参数对激光诱导击穿光谱特征及自吸收效应的影响

为了提高激光诱导击穿光谱技术对微量元素定量分析的精度,降低谱线自吸收效应的干扰,实验以攀钢生铁标准样品中的Mn元素作为研究对象,探索激光诱导击穿光谱特征和自吸收效应随着不同离焦量及延时时间参数的变化规律;通过分析不同延时时间和不同离焦量下等离子体光谱强度、等离子体温度、定标曲线决定系数R²和自吸收系数的变化趋势,来寻找最佳延时时间与最佳离焦量。结果显示,定标曲线决定系数R²随着延时时间的增大总体呈下降趋势,随离焦量的增大是先急剧增加再缓慢减小,在离焦量为-2.5mm时达到最大值0.9988;自吸收系数随延时时间的增大逐渐减小,随离焦量的增加是先增大后减小,在-3.75mm时自吸收效应最弱。综合可得,最佳延时时间条件为2μs左右,最佳离焦量在-2.5~-3.75mm范围内。结果表明,通过不断调整和优化系统参数,能够在一定程度上降低自吸收效应,提高定量分析的精度。该实验为探索系统参数对激光诱导击穿光谱特征和自吸收效应的影响提供了一种新的途径和参考依据。     

基于激光诱导击穿光谱技术的废旧金属分类辨识

废旧金属回收是工业中金属的重要来源之一,是发展循环经济的重要内容。废旧金属产量巨大,通常表面覆盖杂质,凹凸不平,因此对分类方法的判别能力和计算速度提出较高要求。采用激光诱导击穿光谱技术研究分析了7种废旧金属分类识别问题,包括生铝、熟铝、镁、不锈钢、锌、黄铜与红铜。为了符合现场应用条件,实验中每个样本点只激发一次建立并分析了多种分类模型,包括支持向量机(SVM)分类模型,主成分分析方法结合支持向量机(PCA-SVM)分类模型,遗传算法结合支持向量机(GA-SVM)分类模型,遗传算法选择特征光谱结合主成分分析方法和支持向量机(GA-PCA-SVM)分类模型,以及遗传算法选择特征光谱结合主成分分析方法和人工神经网络(GA-PCA-BP)分类模型。通过遗传算法选取包含丰富特征的谱段组合与支持向量机方法相结合建立GA-SVM分类模型,490组验证样本分类准确率为93.47%。为了判断该模型的鲁棒性,对一批新样品,在自研的分选系统上以传送带匀速运行的方式进行测试,获取的750组光谱测试数据,分类准确率为88.27%,证明了该分类模型具有很好的移植性和应用性。     

激光诱导击穿光谱技术结合自吸收修正和偏最小二乘法的铁矿石酸度分析

铁矿石冶炼过程中对其酸度进行准确把控将对铁矿石利用率及冶炼过程产生严重影响。因此,亟需一种铁矿石酸度快速准确分析方法。实验基于激光诱导击穿光谱(Laser-induced breakdown spectroscopy,LIBS)技术结合偏最小二乘回归(Partial least squares regression,PLSR)方法成功地提出了一种铁矿石酸度快速定量分析方法。首先,采集了20组铁矿石样品的LIBS光谱数据,并采用美国国家标准与技术研究院(National Institute of Standards and Technology,NIST)数据库对铁矿石的LIBS特征谱线进行标定。然后,采用内参考线自吸收修正(Internal reference for self-absorption correction,IRSAC)和5折交叉验证分别对光谱数据以及PLSR模型潜变量(Latent variables,LVs)进行优化。最后,基于优化后的光谱数据以及LVs构建了PLSR模型用于预测集铁矿石酸度的分析。结果表明,该模型具有较好的预测性能,其预测集决定系数(R²_p)为0.9784,均方根误差(RMSEP)为2.916%。说明LIBS结合自吸收修正和PLSR法为铁矿石酸度的快速定量分析提供了一种可行的方法。