Spectral Classification of Lignite
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Spectral Classification of Lignite V. I. Butakovaa, *, A. I. Kirillovaa, *, and V. K. Popova, ** a
AO VUKhIN, Yekaterinburg, Russia *e-mail: [email protected] **e-mail: [email protected]
Received April 16, 2020; revised April 16, 2020; accepted May 12, 2020
Abstract—Lignite is classified in terms of its diffuse reflectance IR spectrum, by soft independent modeling of class analogy (SIMCA). Keywords: classification, lignite, simulation, IR spectrum, quantitative analysis DOI: 10.3103/S1068364X20060034
Lignite is widely used in the production of electricity and heat and in sectors such as chemical technology. Coal quality must be monitored in order to ensure safe and effective processing and for commercial purposes. Lignite from different sources differs considerably in properties. In the existing classification, three groups and four subgroups are distinguished [1]. The groups and subgroups combine coal of similar parameters but with different chemical structure and properties. In the classification, the assignment of lignite to a particular class, category, type, and subtype is based on the vitrinite reflection coefficients, the sum of fusinized components, the maximum moisture content, and the yield of semicoking tar. The analytical moisture content and ash content of the coal are also considered. Such analysis cannot be conducted on an ongoing basis. Rank assignment calls for many hours of work by a group of skilled specialists, using special equipment. We need express methods for the classification of lignite on the basis of parameters that are associated with the molecular structure of the organic mass and may be rapidly measured. Such parameters may be derived from the infrared (IR) spectrum of the coal. The Spectrotest system, based on IR spectra, determines the coal parameters required for classification simultaneously [2, 3]. That considerably speeds up the assignment of rank, group, and subgroup. In
comparison with hard coal, lignite is less suitable for IR spectral analysis, because its spectra are less informative. Chemical analysis permits classification based on IR spectral variables [4]. It is of interest to assess the effectiveness of such classification of lignite for spectral rank assignment, without analysis of any genetic or technological parameters. If effective, such a procedure would greatly accelerate coal ranking and permits its automation. In the present work, we consider lignite from two fields: P and L lignite. We know that P lignite is of rank 3BV according to the existing classification, while L lignite is of rank 2BV. Both are of the same category and subtype. For these samples, the parameters used in classification vary within standard limits, and the yield of volatiles and elemental composition of the organic mass cover broad ranges (Table 1). We may expect significant difference in their IR spectra from one instance to another, without change in the rank. The IR spectra of P and L lignite depend on the content of minerals, which fluctuates widely. This complicates the deve
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