Rapid analysis of coal blends by diffuse reflectance FT-i.r. spectrometry

Rapid analysis of coal blends by diffuse reflectance FT-i.r. spectrometry Peter

M. Fredericks*,

BHP Central Research (Received 75 January

Rika Kobayashi

Laboratories, 1987; revised

and Paul R. Osborn

PO Box 188, Wallsend, 23 March 1987)

NSW

2287,

Australia

A method is described for the rapid analysis of coal blends by the treatment of diffuse reflectance Fourier transform infrared (FT-i.r.) spectral data with the computer program CIRCOM (Computerized InfraRed Characterization Of Materials). CIRCOM uses factor analysis of the FT-ix. spectra of a calibration set of samples of known blend proportions to reduce the data set, followed by multiple linear regression to derive correlation equations for the blend components. These correlation equations can then be used to estimate the blend proportions for unknown samples similar to those in the calibration set. The method was demonstrated with a calibration set of synthetic blends of four Australian coals used in the coking blend at the BHI’ Newcastle Steelworks. The standard deviation of the calibration for Metropolitan coal, the high rank component of the blend, was 0.68 wt %. Four months after calibration, the correlation for wt “/oMetropolitan coal was tested with a further 35 blend samples. Good agreement was found and the RMS difference between actual and estimated results was 1.78 wt “/,. After calibration, the method is fast and sample preparation is simple. (Keywords:

analysis of coal; FT-i.r.;

coal blends)

Modern cokemaking practice generally requires the blending of a number of coals of differing properties to achieve blast furnace coke of the correct quality at an economic cost. Such blending is carried out on a large

scale and must be done carefully to produce coke of a consistent quality. To ensure consistent blending, the coal stream to the coke oven should be properly sampled and the components of the blend constantly monitored. While this has been recognized, it has not been common practice because of the difficulty of analysing coal blends. The conventional method of coal blend analysis is the petrographic technique of optical microscopy and point counting’. A crushed sample (nominal topsize 1 mm) of the blend is set in epoxy resin, a face through the coal is polished and viewed under an optical microscope. Generally, the microscope has an automated stage which allows a large number of different tields of the sample to be viewed sequentially. At each field the operator assigns the coal particle in the centre of the field to a particular component of the blend on the basis of reflectance and morphology, which are different for coals of differing rank. After a large number of fields (say 50&1000 coal points) have been viewed, an estimate of the volumetric analysis of the blend is obtained. The procedure of optical point counting is time-consuming and is subject to statistical counting errors. It also relies on the subjective judgement of the individual operator when assigning particular coal particles to blend components. Attempts have been made to overcome the problem of operator subjectivity in optical point counting by using automatic systems based on the measurement of reflectance distributions. These systems have used

* Present address: Milton.

Perkin-Elmer Qld 4064. Australia

Instruments,

001~2361/87,‘111603-06S3.00 0 1987 Butterworth & Co. (Publishers)

Ltd.

301 Coronation

Drive,

automated reflectance measurement with microscopes’ or with image analysers 3-4. However, sample preparation is still time-consuming, measurement times remain relatively long and the accuracy of the determination is acceptable only for simple blends of widely differing coals. A completely different approach was used by Grifliths and co-workers5,6 involving diffuse reflectance Fourier transform infrared (DRIFT) spectrometry. Despite the optical inefficiency of the technique, diffuse reflectance measurements of solid samples have become routine because of the advent of Fourier transform infrared (FTi.r.) spectrometers which are significantly more sensitive than conventional dispersive spectrometers. Griffiths and co-workers treated the raw reflectance data from neat samples with the Kubelka-Munk function’ to achieve a partial linearization. They then measured the ratio of the intensity of the aromatic C-H stretching band near 3050 cm- ’ to that of the aliphatic C-H stretching band near 2950 cm I. This ratio was found to vary for binary coal blends of high and low volatile coals. In one case the relationship was non-linear’, but in a second case a reasonably linear plot was obtained6. While this infrared method is considerably faster than petrographic methods for similar levels of accuracy, it is limited to binary blends because only two points in the spectrum are used. This paper reports another approach to coal blend analysis by FT-i.r. spectrometry. The method uses an infrared data processing package called CIRCOM (Computerized InfraRed Characterization of Materials)8 ’ ’ to relate the composition of the sample to its infrared spectrum, using the mathematical technique of factor analysis. Because CIRCOM uses large regions of the FTi.r. spectrum, or indeed the whole spectrum, it is not restricted to binary blends. The FT-i.r. method was demonstrated using a typical coking blend composed of four coals from South-Eastern Australia.

FUEL, 1987, Vol 66, November

1603

Rapid

analysis

of coal blends

by diffuse

reflectance

FT-i.r.

spectrometry: Table 1

Typical

P. M. Fredericks analyses

multisampler attached to Nicolet IO-MXE FT-ir.

EXPERIMENTAL FT-i.r.

spectrometrq

Spectra were obtained in diffuse reflectance on a Nicolet lo-MXE FT-i.r. spectrometer equipped with a Harrick DRA-3CM diffuse reflectance accessory, at a nominal resolution of 2 cm ‘. Details of experimental procedures have been given elsewhere”. An automatic sample changer (Figure I), fabricated in-house, was used. This allowed the instrument to run unattended and also ensured that all samples were presented to the reflectance accessory at precisely the same position and height. This has been a major factor in obtaining reproducible diffuse reflectance spectra. Spectral data were transferred to a VAX 11/750 minicomputer for treatment by CIRCOM software. All data processing was carried out on the raw reflectance data. The Kubelka-Munk function was not used. Sumples

Initially, 67 samples of coke oven feed, of nominal topsize 6 mm, were obtained from Newcastle Steelworks over a period of about three months from November 1983 to February 1984. The blend consisted of four components defined by the colliery name, Stockton Borehole, Lambton, John Darling and Metropolitan. The first three coals are high volatile bituminous from the Newcastle coal measures. Metropolitan is a low volatile higher rank coal from the Bulli seam in Southern New South Wales. The three coals from the Newcastle area are very similar, however the Stockton Borehole is somewhat different from the other two in its ash analysis and coking properties. Typical analyses for these coals are given in Tab/e I. At the Newcastle Steelworks the most significant analysis is the proportion of the high rank Metropolitan coal in the blend. Further samples of the individual coals were obtained over a six month period. These samples, of nominal topsize 6 mm, were washed coals which had passed through a coal preparation plant. Synthetic

blend preparation

The individual coals were pulverized to a nominal topsize of 76 pm. Blends containing 2, 3 or 4 of the coals were prepared by weighing the materials into a plastic

1604

FUEL, 1987,

Vol 66, November

for the coals used in the synthetic

blends

Metropolitan

Stockton Borehole

Lambton and John Darling

Seam(s)

Bulli

Young Wallsend, Borehole

Dudley, Victoria Tunnel

Moisture (adb) Volatile matter (daf) Ash (db) Carbon (daf) Hydrogen (daf) Nitrogen (daf) Oxygen (daf) Reflectance (R, max) Silica in ash (wt 0;) Alumina in ash (wt If/,,)

0.9 22.6 10.7 88.9 4.78 1.6 4.2 I .27 55.9 35.9

2.5 40.2 IO.4 83.3 5.47 2.0 8.6 0.82 58.6 28.4

2.x 39.1 IO. I 83.6 5.57 2.2 8.3 0.82 72.0 14.8

Colliery

Figure 1 Photograph of diffuse reflectance Harrick diffuse reflectance accessory and spectrometer

et al.

adb = air dried basis; db = dry basis: daf = dry ash-free

basis

vial, to a total weight of 10 g. The sealed vial was shaken thoroughly and then attached to a horizontal rod which was slowly turned for _ 10 min to ensure complete blending of the components. Petrographic

analysis

qf‘ blends

The proportion of high rank (Metropolitan) coal in the Newcastle Steelworks coking blend samples was determined by optical microscopy using standard point counting techniques. The remaining component coals of the blend were too similar to be distinguished by optical techniques. 500 points were counted for each sample. The statistical errors involved in point-counted measurements are well understood and can be calculated”. The standard deviation for the measurement (where there are no additional errors in classifying the blend components) for 500 points, performed on the same sample by the same operator, for a blend component present in the range 2(r 50% is - 2 %. For different samples of the same blend and different operators, the standard deviation will be considerably larger’ 2. Treatment

of spectral

data

The CIRCOM* *-’ ’ spectral data processing method, based on factor analysis, was used to derive relationships between the FT-i.r. spectra and the proportion of the various blend components. The 210&300 cm- ’ region of the spectrum, a total of 1864 data points, was used in the calculations. This spectral region was chosen to include most of the absorption bands due to both the organic and mineral matter parts of the coal. Of course, the C-H and O-H stretching bands occur at higher wavenumbers, however these functional groups are represented in the chosen region by absorption bands due to various bending vibrations. Prior to CIRCOM analysis the spectral data were further reduced by averaging each set of 8 data points to yield 233 data points for each spectrum. Averaging has the effect of reducing noise in the spectra, but also leads to an increase in the number of factors required to reproduce the spectra to within experimental error. Many of these factors are not significant and are removed at the regression stage”. CIRCOM requires measured properties, or known * CIRCOM UK

is available

from Perkin-Elmer

Ltd, Beaconsfield,

Bucks,

Rapid

analysis

of coal blends

by diffuse

reflectance

FT-i.r.

spectrometry:

et al.

P. M. Fredericks

Newcastle coals, the smaller clay bands (to its different ash differences, but overall are quite similar.

Stockton Borehole sample shows 3700 cm- ‘) which may be related analysis. There are other minor the spectra of the Newcastle coals

CIRCOM

by optical microscopy

4

I

4400

3200

1

2000

1400

I

800

200

WAVENUMBERS

Figure 2 Diffuse reflectance spectra of neat samples of four Australian coals used in cokemaking. A: John Darling, B: Lambton, C: Stockton Borehole, D: Metropolitan. Spectra are displaced for clarity

proportions of components, for a calibration set of samples in order to generate regression equations which can be used to predict properties of unknown samples. For the Newcastle Steelworks blends only the proportion of Metropolitan coal in the blends could be measured by petrographic methods because of the similar reflectances of the other component coals. For the calibration set of synthetic blends, the proportions of all the blend components were known accurately. RESULTS

calibration

Factor analysis was carried out on the 2100-300 cm- ’ region of the diffuse reflectance FT-i.r. spectra of the 67 samples of coking blend obtained from Newcastle Steelworks. Eighteen significant factors were required to reproduce the spectra to within experimental error according to empirical methods discussed by Malinowski and Howery13. A correlation was derived between the signficant factor loadings and the proportion of high rank coal (Metropolitan) in the blend as determined by optical point counting. The correlation, shown graphically in Figure 3, had a coefficient of determination (R’) of 0.668 and a standard deviation about the mean of 3.4% absolute. While this is a relatively weak correlation, it should be remembered that the error in the point counted measurements, calculated for repeat measurements on the same sample block, is -2% absolute” and this contributes significantly to the standard deviation of the regression. In view of the speed of the FT-i.r. determination and the large error involved in optical microscopy, a standard deviation of 3.4% might be acceptable for the determination of the proportion of high rank coal in the blend. However, the predictive ability of a correlation is always worse than the standard deviation obtained for the calibration set because of unwanted relationships between samples within the calibration set. Realistically, the predictive standard deviation for this correlation is likely to be of the order of 45% absolute, which is unacceptably high.

AND DISCUSSION

FT-i.r. spectrometry Diffuse reflectance spectra of neat coal are known to be grossly distorted. There is a severe saturation effect, particularly in the region 1700-200 wavenumbers. In this region the spectra are non-linear and Beer’s Law will not be obeyed. Where linear spectra are required, the sample is generally diluted with a large amount of a nonabsorbing material such as potassium bromide. To further linearize the data the Kubelka-Munk function may be applied. The dilution technique is not optimum for rapid quality control purposes because accurate weighing and mixing of the materials is required. For this reason, the work reported in this paper used the raw reflectance data of neat samples despite the known nonlinearity. Reflectance spectra of samples of each of the four component coals in the Newcastle steelworks blend are shown in Figure 2. The spectra were obtained using finely powdered caesium iodide as reference. Each spectrum has a maximum reflectance of -45 y0 and a minimum reflectance - 5 %, relative to caesium iodide. The spectrum of the high rank Metropolitan coal can be seen to be quite different from those of the Newcastle coals. In particular, the carboxylic O-H absorption (- 380&2200 cm-‘) is while the aromatic C-H stretching less intense, absorption (near 305Ocn- ‘) is much more intense. For the Diffuse reflrctance

a”

.’ :i

45 -

40 -

35-

30-

20

25

30

35

VOL % METROPOLITAN Figure 3 CIRCOM calibration the proportion of Metropolitan optical microscopy

40

(BY OPTICAL

45

50

MICROSCOPY)

plot for 67 coking blend samples using coal in the blend as determined by

FUEL, 1987, Vol 66, November

1605

Rapid analysis of coal blends by diffuse reflectance Table 2 Australian

Proportions of components coals used as the calibration

Metropolitan

Stockton Borehole

10

90

(wt:;) set

for

Lambton

63 blends

of 4

John Darling

90

10 10 10 10 10 10 15 15 15 15 15 15 15 20 20 20 20 20 20 20 25 25 25 25 25 25 25 30 30 30 30 30 30 30 35 35 35 35 35 35 35 40 40 40 40 40 40 40 45 45 45 45 45 45 45 50 50 50 50 50 50 50

30 45 45

30 45 45

90 30 45 45

85 85 28.3 42.5 42.5

28.3 42.5 42.5

85 28.3 42.5 42.5

80 80 26.1 40 40

26.7 40 40

80 26.7 40 40

75 75 25 37.5 37.5

25 37.5 37.5

70

75 25 37.5 37.5 _

70 23.3 35 35

23.3 35 35

70 23.3 35 35

65 65 21.7 32.5 32.5

21.7 32.5 32.5

65 21.7 32.5 32.5

60 60 20 30 30

20 30 30

55 _~ _ 18.3 27.5 27.5

60 20 30 30

55 18.3 27.5

55 18.3 _

27.5

27.5 27.5

50 50 _ 16.7 25 25

16.7 25 25

CIRCOM

50 16.7 25 25

calibration by synthetic blends

An alternative method for carrying out the CIRCOM calibration would be to use synthetic blends made from the four component coals- used in the Newcastle Steelworks blend. This would remove errors associated with the point counting determination of the blend

1606

FUEL, 1987,

Vol 66, November

FT-i.r. spectrometry:

P. M. Fredericks

et al

components. To test this hypothesis a number (63) of blends were made (see Table 2) and their diffuse reflectance FT-i.r. spectra obtained. Factor analysis of the 2100_3OOcm-’ region of the spectra showed that 18 factors were required to reproduce the spectra to within experimental error. CIRCOM correlations were obtained between the significant factor loadings and the known proportions for each of the four component coals. Details of these correlations are given in Table 3 and they are also shown graphically in Figure 4. Tuble 3 shows that the standard deviation about the mean for the regression for the proportion of high rank Metropolitan coal (0.68 “/:, absolute) is very much lower, by a factor of about 5, than that obtained when point counting techniques were used. The standard deviation obtained for Stockton Borehole coal (1.36%) is also relatively low and could prove useful for the analysis of that component in a blend. The results for the remaining components, Lambton and John Darling, are considerably worse (3.09 % and 3.28 T;, respectively) and are unlikely to prove useful for determining these components. This result is not surprising since Lambton and John Darling are very similar coals with almost identical spectra and can be considered together as a single component. Therefore, if both the Metropolitan and Stockton Borehole components of the Newcastle blend can be determined to a reasonable accuracy, then the sum of the Lambton and John Darling components is available by difference. Prediction qf unknown blends In order to predict the blend proportions in an unknown sample, the CIRCOM program calculates the factor loadings for the unknown FT-i.r. spectrum using the factors from the calibration set. These factor loadings are then entered into the regression equations derived for the various blend components and the estimate of each of the blend components of interest can then be calculated. A separate part of the program uses the Mahalanobis distance to confirm that the unknown spectrum is similar to the spectra forming the calibration set, and also calculates a 95”j, confidence interval for the predicted value”. The CIRCOM correlations achieved for the coal blends were tested with a number of synthetic blends, most of which were different from those in the calibration set. Initially, 5 simple binary blends of Metropolitan and Stockton Borehole coals were made and the proportion of Metropolitan coal was estimated using the CIRCOM regression. The coal used for these simple blends was obtained about one month after the coal used for the calibration set blends. Figure 5 shows a plot of actual wt “/, Metropolitan coal against the proportion of Metropolitan coal estimated by the CIRCOM procedure. The results are in very good agreement and the root mean square (RMS) difference is 0.85 ‘?{. A much larger test set of blends was assembled using coals obtained about 4 months after those used in the calibration set. The object was to check if the calibration would hold for a significant time period. It is possible that coals, even those from single seams or mines, may change slightly as mining progresses and this might affect the validity of the calibration. Thirty-five binary, ternary and quaternary blends of the four coals under test were prepared. The proportion of Metropolitan coal was

Rapid

analysis

of coal blends

by diffuse

.

reflectance

FT-i.r.

spectrometry:

P. M. Fredericks

.

et al.

. . .

65

4c 1 -

1= ci-

-lC )_ -10

I

40

ACTUAL

95

JOHN

I

I

I

I

15

DARLING

40

15

-10

90

65

ACTUAL

(WT%)

C . .

.

LAMBTON

(WT%)

551

.

--I

D

1 !

t

70

90

65

I

b . .

s

35

l

!

45

t

25

t 15

t t

-5

20

ACTUAL

70

45

STOCKTON

BOREHOLE

95

(WT%)

5

15

ACTUAL

25

35

METROPOLITAN

45

(WT%)

Figure 4 CIRCOM calibration plots for the four component coals of 63 synthetic coking blends made in the laboratory. A: John Darling, B: Lambton, C: Stockton Borehole, D: Metropolitan. For occasions when there is none of a particular component in the blend, CIRCOM can predict a small negative value

Table 3 CIRCOM regressions for a calibration set of 63 synthetic coal blends. The 210@3OOcm~ region of the FT-i.r. spectra was used _~___. Component coal

No. terms in regression equation

Coefficient of determination CR’)

Standard deviation

Metropolitan Stockton Borehole Lambton John Darling

12 11 11 10

0.998 0.998 0.988 0.986

0.68 1.36 3.09 3.28

varied from 10 to 50 wt %. Diffuse reflectance FT-i.r. spectra of the blends were obtained and used as unknowns in the CIRCOM program. The estimated results for wt y0 Metropolitan coal, the most significant

coal in the blend for coking purposes, are shown plotted against the actual values in Figure 6. Again, there is reasonable agreement between the actual values and those obtained from the FT-i.r./CIRCOM method, although the RMS difference for these results is higher at 1.78 %, perhaps indicating a minor change with time of one or more of the coals. This level of accuracy is sufficient for blend control purposes, particularly since there is, at the present time, no other rapid coal blend analysis method available. A further advantage of CIRCOM is that other properties of the coking blend, such as wt % ash, or volatile matter, can also be estimated simultaneously with the blend proportions from the same FT-i.r. spectrum,

FUEL, 1987, Vol 66, November

1607

Rapid

analysis

of coal blends

by diffuse

reflectance

FJ-i.r.

spectrometry:

P. M. Fredericks

et al.

60

50

,...,i . ,.’ ,a.’

40

1

2

s

30 -

F Y

20 -

2

.

:

30

::

: j:

20

.*’

: 10 t 0 *’

0

:

:

.*

!

10

1

I

20

10

ACTUAL

.)’

.’

I

I

I

30

40

50

METROPOLITAN

0

f

0

(WT%)

Figure 5 Plot of proportion of Metropolitan coal estimated by the FTi.r./CIRCOM method against actual proportion for a prediction test set of 5 binary blends of Stockton Borehole and Metropolitan coals. RMS difference = 0.85 wt “/L

I

I

I

I

1

10

20

30

40

50

ACTUAL

METROPOLITAN

1

60

(WT%)

Figure 6 Plot of proportion of Metropolitan coal estimated by the FTi.r./CIRCOM method against actual proportion for a prediction test set of binary, ternary and quaternary blends of Australian coals. RMS difference = 1.78 wt %

REFERENCES provided that these properties are known for the samples in the calibration set’-’ i. Although the data processing reported here was performed on a mini-computer, most small FT-i.r. spectrometers now have computers of sufficient power to run programs of the size of CIRCOM. After calibration, unknown samples of coal blends can be analysed in m 40 min, including sample preparation, which is merely size reduction to N 1OO~m. With a more modern spectrometer a decreased data collection time reduces the overall analysis time to -25 min, without loss of accuracy.

1

2 3 4 5 6 7 8 9 10

ACKNOWLEDGEMENTS The authors express their appreciation to R. Van Den Heuvel for technical assistance, and to the Broken Hill Proprietary Co. Ltd for permission to publish this work. Thanks are also due to J. B. Lee and C. Coin for valuable discussions.

1608

FUEL, 1987,

Vol 66, November

11 12

13

‘Analysis of Blends of Coals of Different Rank’, International Handbook of Coal Petrography, Supplement to 2nd Edn, Centre National de la Recherche Scientitique, Paris, 1971 Gray, R. J. and Rhoades, A. H. Proc. Ironmaking Conf: 1984,43, 189 Riepe, W. and Stellar, M. Fuel 1984, 63, 313 Lee, J. B. J. Microsc. 1985, 137, 137 Lowenhaupt, D. E., Griftiths, P. R., Fuller, M. P. and Hamadeh, I. M. Proc. Ironmaking Conf. 1982, 41, 39 Fuller, M. P., Hamadeh, I. M., Gritliths, P. R. and Lowenhaupt, D. E. Furl 1982,61, 529 Kubelka, P. and Munk, F. Z. Tech. Phys. 1931, 12, 593 Fredericks, P. M., Osborn, P. R. and Swinkels, D. A. J. Fue/ 1984, 63, 139 Fredericks, P. M., Lee, J. B.,Osborn, P. R. and Swinkels. D. A. J. Appl. Spectrosc. 1985, 39, 303 Fredericks, P. M., Lee, J. B., Osborn, P. R. and Swinkels, D. A. J. Appl. Spectrosc. 1985, 39, 311 Fredericks, P. M., Osborn, P. R. and Swinkels, D. A. J. Anal. Chem. 1985,57, 1947 ‘Determination of the Maceral Group Composition of Bituminous Coal and Anthracite (Hard Coal)‘, Standards Association of Australia, AS 251551981 Malinowski, E. R. and Howery, D. G. ‘Factor Analysis in Chemistry’, Wiley, New York, 1980, Ch 4, pp. 72-86

Filmset by Mid-County Press, London SW15 Printed by Henry Ling Ltd. Dorchester, Dorset