Ranking of Indian Coals using Image Analysis Technique By Niraj Kumar Software Developer Kolkata ' 700026. West Bengal, India E-mail: nirajkumariitkgp@gmail.com
Contact No: (Mobile).
© 2003 Niraj Kumar. All rights reserved.
Abstract
In this paper, an attempt has been made to rank Indian coal using Image analysis
technique. Coal apart from C (carbon) contains number of other constituent like
hydrogen, nitrogen, sulphur, oxygen etc. Classifying coal scientifically is of tremendous
importance in techno-economic applications particularly for the purpose of
grading/pricing, for quality grouping , for reserve estimation and for industrial use. In this
study, image analysis coupled with Energy Dispersive Spectrometry (EDS) analysis on a
Scanning Electron Microscope (SEM) is proposed to apply for ranking of Indian coal as
well as for estimating degree of coal liberation for metallurgical purpose.
Screened size fractions of coal were mounted on polished thin sections and later on
analyzed by a SEM coupled with EDS. This is important for discrimination of various
constituent of coal, particularly when two constituent have similar average atomic
numbers, such as carbon and nitrogen. Two images per field were collected '
backscattered electrons image and a multi-element X-ray dot mapping images. The
results were utilized for ranking of coals as well as for liberation analysis of various
coals.
Introduction
Coal quantification and liberation degree evaluations are a major issue for ranking of coal
as well as its characterization for mineral dressing for customer required quality delivery.
These analyses can be performed manually by optical microscopy (OM) or a Scanning
Electron Microscope (SEM) in a very tiresome and exhaustive routine. Image analysis
coupled with an OM or a SEM can perform these analyses resulting in more reliable and
rapid outcomes.
Since phase differentiation by OM coupled to an image analysis is not a usual
and easy task, a digital SEM image is frequently used to solve more complex
mineralogical associations. Special care must be taken regarding sample preparation
and beam control . Atomic number contrast from backscattered electrons (BSE)
signal are primarily used for phase discrimination; however, when phases with a very
similar average atomic number are present, X-ray information is the only possible tool
that could be used to differentiate them.
This work presents an off-line image analysis routine applied to the
characterization of Indian coal. However, the BSE image not able to clearly identify between
phases having similar atomic numbers like C and N. These phases could only be properly
segmented by coupling additional information related to their chemical composition
using X-ray data. Multi-element X-ray dot-mapping images acquired by an energy
dispersive spectrometry (EDS) were considered for this purpose.
Methodology
The study samples consisted of coal sample particles from four closely screened
fraction sizes mounted on polished thin sections. Special care needs to be taken regarding the
sample preparation to avoid the physical touch of particles as well as regarding the
polishing surface quality.
BSE and X-ray dot images need to obtained by a S440, Leo, coupled with an Isis-
300 EDS System, Oxford. X-ray dot-mapping images also needed to be acquired by S440;
each selected element was represented by a binary plane and by a specific gray level value.
Both images, presenting 1024 by 768 pixels resolution, needed to be processed off-line by
Quantimet Qwin-Pro software, Leica, an image analysis system which operates under the
same SEM PC hardware. Important stages involved in the study are:
Stage 1:
In order to determine all constituent of coal, qualitative mineralogical workis needed to be first performed coupling X-ray diffraction data with a detailed SEM-EDS
observation. This helps us in identifying various constituent of coal like C, H, O, N, P, S etc.
Stage 2:
The second step comprised the acquisition of BSE and X-ray dot-mappingimages. Since the acquisition time for the dot images were relatively high, off-line
image processing was chosen to assure a better SEM electron beam stability during the
total acquisition period, which corresponds to almost 200 minutes for 30 fields per
sample. Incident probe current, brightness and contrast levels were set to allow the
acquisition of BSE and X-ray images with a good quality for further processing.
Because particle density per field is one of the major factors that directly affect
the total processing time, an ideal compromise is required to optimize the acquisition
time. The SEM magnification was adjusted for an average of 40 to 50 particles per
field, a situation in which some particles may touch other particles. For this reason, the
basic step in image processing is to individualize these touching particles.
Stage 3:
A relatively complex subroutine should be applied todiscriminate the touching particles. Firstly, the detected image was eroded
and then skeleton and prune operations were applied in order to separate the
particles so they would not touch each other. Finally applying outline followed by
close and open operations to the particles may result in the dark lines of potential
touching areas. These lines should be subtracted from detected image by
logical operation, resulting in the final binary image of particles to be measured.
An image analysis routine should be developed in order to discriminate the various constitute
of coal and, later on, to perform modal and mineral liberation analysis. Detection,
identification and segmentation of the phases are the most complex issues, and the
routine should process a gray scale image plus external inputs as the X-ray dot image.
Gray level threshold from the BSE image can allow discriminating up to 6 binary
planes. Further, The acquired multi-element X-ray dot-mapping image needs to be submitted
to a gray level threshold that was intended to discriminate various constituent of coal.
Stage 4:
At the end of the segmentation procedure each mineral phase was representedby a binary image plane. Modal or quantitative phase analysis could be then performed
considering the area fraction measurements for the different binary planes (mineral
phase). The results of all fields should be accumulated in a file and, later on,
normalized to 100% regarding the volume percentage. The weight percentages are calculated
considering the mineral densities and their volume fractions.
This way, we able to find the various
constituent of coal and their composition and able to rank the various Indian coal on the basis
of quality and composition. Also, we able to do liberation analysis which helps to determine
suitable method for its beneficiation.
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