Research on a LIBS-based detection method of medium-and-low alloy steel hardness

Hu, Jun; Yang, Liang; Lin, Tung-Yi; Shi, Hongyang; Qiao, Peng; He, Yong; Liu, Yande

doi:10.1039/d2ja00255h

Cited by 4 publications

(2 citation statements)

References 18 publications

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“…Si-PLS mainly included the following steps: (1) the partial least squares model of global variables was established; (2) the global variable was divided into 20 sub-intervals, and the regression models of spectral data in each sub-interval were established; (3) the results of steps ( 1) and (2) were compared, and the sub-interval with the best result was taken as the selection sub-interval; (4) the sub-interval selected in step (3) was taken as the central interval, and the variable region was expanded to both sides; and (5) four sub-intervals with better detection performance in the same partition were combined to complete the screening of synergy sub-intervals. UVE was a variable screening algorithm based on the analysis of a partial least squares regression coefficient, which mainly eliminated the variables that could not provide useful information [38]. The main principle of UVE was to combine the artificially generated noise matrix with the spectral matrix and TN reference value matrix to form a new matrix, through which the useless information threshold could be obtained, and then the useful information variables could be screened by comparing the stability of the regression coefficient with the decision threshold [39].…”

Section: Selection Of Spectral Featuresmentioning

confidence: 99%

Rapid and High-Performance Analysis of Total Nitrogen in Coco-Peat Substrate by Coupling Laser-Induced Breakdown Spectroscopy with Multi-Chemometrics

Lu,

Wang,

et al. 2024

Agriculture

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Nitrogen is an important nutrient element for crop growth. Rapid and accurate acquisition of nitrogen content in cultivation substrate is the key to precise fertilization. In this study, laser-induced breakdown spectroscopy (LIBS) was used to detect the total nitrogen (TN) of coco-peat substrate. A LIBS spectrum acquisition system was established to collect the spectral line signal of samples with wavelengths ranging from 200 nm to 860 nm. Synergy interval partial least squares (Si-PLS) algorithm and elimination of uninformative variables (UVE) algorithm were used to select the spectral data of TN characteristic lines in coco-peat substrate. Univariate calibration curve and partial least squares regression (PLSR) were used to build mathematical models for the relationship between the spectral data of univariate characteristic spectral lines, full variables and screened multi-variable characteristic spectral lines of samples and reference measurement values of TN. By comparing the detection performance of calibration curves and multivariate spectral prediction models, it was concluded that UVE was used to simplify the number of spectral input variables for the model and PLSR was applied to construct the simplest multivariate model for the measurement of TN in the substrate samples. The model provided the best measurement performance, with the calibration set determination coefficient (RC2) and calibration set root mean square error (RMSEC) values of 0.9944 and 0.0382%, respectively; the prediction set determination coefficient (RP2) and prediction set root mean square error (RMSEP) had values of 0.9902 and 0.0513%, respectively. These results indicated that the combination of UVE and PLSR could make full use of the variable information related to TN detection in the LIBS spectrum and realize the rapid and high-performance measurement of TN in coco-peat substrate. It would provide a reference for the rapid and quantitative assessment of nutrient elements in other substrate and soil.

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Section: Selection Of Spectral Featuresmentioning

confidence: 99%

Rapid and High-Performance Analysis of Total Nitrogen in Coco-Peat Substrate by Coupling Laser-Induced Breakdown Spectroscopy with Multi-Chemometrics

Lu,

Wang,

et al. 2024

Agriculture

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“…Two reports from the same research group discussed the determination of the hardness of train wheel steels using LIBS. 19,20 Conventional methods (e.g. the Vickers hardness test) use the depth of an indentation as a measure of hardness.…”

Section: Ferrous 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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Rapid quantitative analysis of multiple rare earth elements in NdFeB alloys based on laser-induced breakdown spectroscopy (LIBS) and random forest (RF)

Zhou,

Hu,

Ren

et al. 2024

Spectrochimica Acta Part B: Atomic Spectroscopy

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Research on a LIBS-based detection method of medium-and-low alloy steel hardness

Abstract: Objective: Hardness is an important physical property of metal materials, which directly affects the mechanical properties of metal materials as key components. Therefore, the detection of hardness is of great...

Cited by 4 publications

References 18 publications

Rapid and High-Performance Analysis of Total Nitrogen in Coco-Peat Substrate by Coupling Laser-Induced Breakdown Spectroscopy with Multi-Chemometrics

Rapid and High-Performance Analysis of Total Nitrogen in Coco-Peat Substrate by Coupling Laser-Induced Breakdown Spectroscopy with Multi-Chemometrics

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

Rapid quantitative analysis of multiple rare earth elements in NdFeB alloys based on laser-induced breakdown spectroscopy (LIBS) and random forest (RF)

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