Rapid classification of coal by laser-induced breakdown spectroscopy (LIBS) with K-nearest neighbor (KNN) chemometrics

IF 1.3 4区工程技术 Q4 CHEMISTRY, ANALYTICAL

Instrumentation Science & Technology Pub Date : 2022-06-17 DOI:10.1080/10739149.2022.2087185

Zhi Cao, Junjie Cheng, Xiaodan Han, Lianshun Li, Jian Wang, Qingwen Fan, Qingyu Lin

引用次数: 4

Abstract

Abstract It is important to classify coal in the industry to improve its utilization. Herein, coal classification was performed using laser-induced breakdown spectroscopy (LIBS) combined with K-nearest neighbor (KNN) chemometrics. The principal component analysis was used to determine the optimum component of the original data. Eight elements (Al, Fe, Ca, Na, Mg, Si, Ti, and K) were selected as the indices for coal classification, while 11 elements were further divided into four categories as indicators for coal classification using the KNN model. The standard coal samples were divided based upon the ash and volatile values and the elemental content. The results were satisfactory, achieving an optimum accuracy of 97.73%. In contrast to traditional methods, LIBS significantly reduced the analysis time, simplified the process, and maintained high accuracy.

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基于k近邻化学计量学的激光诱导击穿光谱(LIBS)对煤的快速分类

摘要对煤炭进行分类对提高其利用率具有重要意义。在此，使用激光诱导击穿光谱（LIBS）和K近邻（KNN）化学计量学对煤进行分类。主成分分析用于确定原始数据的最佳成分。选择8种元素（Al、Fe、Ca、Na、Mg、Si、Ti和K）作为煤的分类指标，使用KNN模型将11种元素进一步划分为4类作为煤的分级指标。标准煤样品根据灰分和挥发性值以及元素含量进行划分。结果令人满意，达到了97.73%的最佳准确度。与传统方法相比，LIBS显著减少了分析时间，简化了过程，并保持了高准确度。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Instrumentation Science & Technology 工程技术-分析化学

CiteScore

3.50

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： Instrumentation Science & Technology is an internationally acclaimed forum for fast publication of critical, peer reviewed manuscripts dealing with innovative instrument design and applications in chemistry, physics biotechnology and environmental science. Particular attention is given to state-of-the-art developments and their rapid communication to the scientific community. Emphasis is on modern instrumental concepts, though not exclusively, including detectors, sensors, data acquisition and processing, instrument control, chromatography, electrochemistry, spectroscopy of all types, electrophoresis, radiometry, relaxation methods, thermal analysis, physical property measurements, surface physics, membrane technology, microcomputer design, chip-based processes, and more. Readership includes everyone who uses instrumental techniques to conduct their research and development. They are chemists (organic, inorganic, physical, analytical, nuclear, quality control) biochemists, biotechnologists, engineers, and physicists in all of the instrumental disciplines mentioned above, in both the laboratory and chemical production environments. The journal is an important resource of instrument design and applications data.