Quantitative analysis of trace carbon in steel samples using collinear long-short double-pulse laser-induced breakdown spectroscopy

Cui, Minchao; Guo, Haorong; Chi, Yada; Tan, Liang Z.; Yao, Changfeng; Zhang, Dinghua; Deguchi, Yoshihiro

doi:10.1016/j.sab.2022.106398

Cited by 15 publications

(8 citation statements)

References 42 publications

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“…Another LIBS application was presented by Cui et al who have continued with their work using long–short double pulse LIBS . 30 Double pulse LIBS is known to have advantages over single pulse. Many workers use two separate lasers to first vaporise the sample and the second to excite the vapour further.…”

Section: Metalsmentioning

confidence: 99%

Atomic spectrometry update: review of advances in the analysis of metals, chemicals and materials

Clough,

Fisher,

Gibson

et al. 2023

J. Anal. At. Spectrom.

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Section: Metalsmentioning

confidence: 99%

Atomic spectrometry update: review of advances in the analysis of metals, chemicals and materials

Clough,

Fisher,

Gibson

et al. 2023

J. Anal. At. Spectrom.

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“…In metal smelting, LIBS technology is mostly used for detecting the composition of alloys, stainless steel, steel slag, and other components [12][13][14][15][16][17][18]. It is seldom used for detecting the composition of copper slag.…”

Section: Introductionmentioning

confidence: 99%

Detection of Al, Mg, Ca, and Zn in copper slag by LIBS combined with calibration curve and PLSR methods

JIA 贾,

LIU 刘,

PAN 潘

et al. 2024

Plasma Sci. Technol.

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The precise measurement of Al, Mg, Ca, and Zn composition in copper slag is crucial for effective process control of copper pyrometallurgy. In this study, a remote laser-induced breakdown spectroscopy (LIBS) system was utilized for the spectral analysis of copper slag samples at a distance of 2.5 m. The composition of copper slag was then analyzed using both the calibration curve (CC) method and the partial least squares regression (PLSR) analysis method based on the characteristic spectral intensity ratio. The performance of the two analysis methods was gauged through the determination coefficient (R2), average relative error (ARE), root mean square error of calibration (RMSEC), and root mean square error of prediction (RMSEP). The results demonstrate that the PLSR method significantly improved both R2 for the calibration and test sets while reducing ARE, RMSEC, and RMSEP by 50% compared to the CC method. The results suggest that the combination of LIBS and PLSR is a viable approach for effectively detecting the elemental concentration in copper slag and holds potential for online detection of the elemental composition of high-temperature molten copper slag.

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“…As a result, LIBS is widely used to explore chemical composition in the industry [6][7][8], space [9,10], underwater [11,12], and geology [13,14] fields, among others. Our research group [15][16][17] also conducted related research on long-short double-pulse laser-induced breakdown spectroscopy technology, and performed a quantitative analysis of steel. LIBS has the advantages of a wide range of analyzable elements, low requirements for the preparation of the substances to be tested, rapid real-time online detection, and high accuracy of quantitative analysis.…”

Section: Introductionmentioning

confidence: 99%

Classification of Aviation Alloys Using Laser-Induced Breakdown Spectroscopy Based on a WT-PSO-LSSVM Model

et al. 2022

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It is well-known that aviation alloys of different grades show large differences in mechanical properties. At present, alloys must be strictly distinguished in the manufacturing plant because their close appearance and density are easily confused In this work, the wavelet transform (WT) method combined with the least squares support vector machine (LSSVM) is applied to the classification and identification of aviation alloys by laser-induced breakdown spectroscopy (LIBS). This experiment employed six different grades of aviation alloy as the classification samples and obtained 100 sets of spectral data for each sample. This research included the steps of preprocessing the obtained spectral data, model training, and parameter optimization. Finally, the accuracy of the training set was 99.98%, and the accuracy of the test set was 99.56%. Therefore, it is concluded that the model has superior generalization capacity and portability. The result of this work illustrates that LIBS technology can be adopted for the rapid identification of aviation alloys, which is of great significance for on-site quality control and efficiency improvement of aerospace parts manufacturing.

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Quantitative analysis of trace carbon in steel samples using collinear long-short double-pulse laser-induced breakdown spectroscopy

Cited by 15 publications

References 42 publications

Atomic spectrometry update: review of advances in the analysis of metals, chemicals and materials

Atomic spectrometry update: review of advances in the analysis of metals, chemicals and materials

Detection of Al, Mg, Ca, and Zn in copper slag by LIBS combined with calibration curve and PLSR methods

Classification of Aviation Alloys Using Laser-Induced Breakdown Spectroscopy Based on a WT-PSO-LSSVM Model

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