KR100928977B1 - Method for Analyzing Coking Characteristics of Coal by Non-Coking Method - Google Patents

Abstract

The present invention is a non-drying coal method for measuring cold strength (DI 150), reaction rate (CRR), hot strength (CSR) which is one of the characteristics of coke when coking coal, a raw material for producing coke, by coking by high temperature dry distillation method. It relates to a method of analyzing the coking property of.

To this end, the present invention is limited to the infrared wavelength measurement range of the coal sample to a value of 450 ~ 4000cm-¹, the step of measuring the chemical structure of this range, and the sample cup for measuring the coal sample in the cup hole slope of 8-12 Mounted on a Fourier transform infrared spectrometer to achieve °, to obtain the highest reproducibility and the least deviation spectrum, and using spectral information reproducibly measured in the infrared wavelength measurement range 450 ~ 4000cm-¹ region of the coal sample It is a step of measuring the calibration model to analyze the coke characteristics of coal samples, and provides a method of analyzing the coking characteristics of coal by the non-drying method that analyzes the coke characteristics cold strength, reaction rate and hot strength.

The present invention obtains the effect of predicting the coking characteristics in a simple way without distilling coal, and also considerably removes the coal distillation facilities and physical measuring devices necessary for measuring the cold strength, reaction rate and hot strength of the coke. It works.

Coke, Non-CO2, Electric Furnace, Infrared Spectrometer, Sample Cup, Coal Sample, Spectrum

Description

METHODS WITH MEANS FOR ANALYZING COKE PROPERTY OF COAL WITH NON-CARBONIZATION}

1 is a conceptual diagram showing the drying and testing process of coal for the conventional coke characteristics analysis;

2 is a perspective view of an infrared spectroscopy apparatus used in a method for analyzing coking characteristics of coal by a non-drying method according to the present invention;

3 is a perspective view of a sample cup installed in an infrared spectrometer used in a method for analyzing coking characteristics of coal by a non-drying method according to the present invention;

4 is a graph showing the coal infrared spectrum and wavelength range used in the calibration model development of the present invention;

5 is a graph illustrating a multivariate calibration model for the coke characterization of coal obtained through the coking characteristics analysis method of coal by the non-drying method according to the present invention.

The present invention relates to a method for analyzing the coking characteristics of coal by a non-drying method, and more particularly cold strength (DI 150), which is one of the characteristics of coke when coking coal, a raw material for producing coke, by high-temperature drying method. ), A method of analyzing coking characteristics of coal by a non-drying method of measuring the reaction rate (CRR) and the hot strength (CSR).

Since steel coke has the purpose of maintaining breathability and supplying heat sources in blast furnaces, the coke characterization value of coal used in coke production is the most important basic data in the blending technology.

As shown in Fig. 1, in the prior art, after producing a test coke according to the tubular test method of the JIS M 88 standard to know the characteristics of the coke, the coke quality by performing physical tests such as cold strength, reaction rate, hot strength of the coke The method of grasping was used.

Referring to Fig. 1, the conventional pipe test method is to collect about 100 kg of coal sample (1), crush it to a specified particle size (3 mm or less), and put it in an 18 L empty paint container (2) in a coke oven at about 1250 ° C. Drying for about an hour gives lump coke (5).

The coke thus obtained was subjected to rotational strength test method according to KS E 3271 by rotating the coke into the cylindrical drum (6) for 150 rotations, and then using the weight ratio of the coke remaining without breaking as the cold strength index (DI 150: Drum Index). do.

In addition, the coke was put into a high-temperature electric furnace (7) of 1100 ° C and reacted with CO2 gas, and the coke weight ratio oxidized was used as the reaction rate (CRR: Coke Reaction Ratio).

After the reaction rate test, the remaining coke is put into the I-type drum tester 8 as it rotates about 600, and then the weight ratio of the coke remaining without breaking is used as a Coke Strength after Reaction (CSR) index.

However, in the conventional analytical method, in order to know the characteristics of the coke of the coal, the pipe-drying test should be carried out, and a coke oven or a large test furnace for physical measurement is required. There was a problem that can be analyzed only if you have a type drum and an electric furnace.

In order to solve the above problems, the present invention eliminates all of the coal distillation process and complex physical measurement device to determine the cold strength, reaction rate, and hot strength after coking, which is the coking property of coal, and the infrared absorption spectrum of coal. It provides a method for analyzing the coking characteristics of coal by non-drying method that can measure the coke cold strength (DI150), reaction rate (CRR), and hot strength (CSR) index simultaneously when the coal is coked. There is this.

In order to achieve the above object, the present invention is to measure the spectrum of the coal sample with an infrared wavelength range of 450 ~ 4000cm-¹, the inclination of the sample cup containing the coal sample is 8 ~ 12 °, and the measurement Converting the spectrum such that the absorption intensity of the converted spectrum has a linear correlation with the concentration of the coal sample, and quantifying the spectral information to obtain a correlation with the coking property from the converted spectrum; The present invention provides a method of analyzing the coking characteristics of coal by a non-drying method that analyzes the cold strength, reaction rate, and hot strength of the coke.

Hereinafter, with reference to the accompanying drawings will be described in detail through the embodiment the configuration and operation of the present invention.

As shown in Fig. 2 to 5, the infrared spectral information of coal shows a close correlation with the coking property.

By developing a calibration model for analyzing the coke characteristics of coal, it is possible to analyze the cold strength (DI150), reaction rate (CRR) and hot strength (CSR) when coal is coked by measuring infrared spectrum of coal.

In the first step of the present invention, the infrared wavelength measurement range of the coal sample was limited to 450 ~ 4.000 cm-¹.

The chemical structure of coal is known to be very complicated, and FIG. 4 is a spectrum of coal appearing in the infrared wavelength range of 450 to 4,000 cm-¹, and [Table 1-1] shows the types of functional groups in which infrared absorption bands appear depending on the wavelength range. It was investigated.

Table 1-1

Wavelength (cm-¹) Functional group 600-900 Aromatic CH out-of-plane bending 1200-1400 CH3, C = O stretching; OH bending 1400-1600 CH2, CH3 bending 1500-1700 Aromatic ring stretching 1700-1900 C = O stretching 2700-3000 Aliphatic CH stretching 2900-3100 Aromatic CH stretching 3200-3600 OH groups

In addition, as shown in [Table 1-1], the infrared spectrum of the coal sample shows that all the functional groups of the chemical components of coal exist within the wavelength range of 600-3,600 cm-¹. It acts as an important factor in limiting the wavelength range.

In order to limit the infrared wavelength region of the coal required for the present invention, the correlation with the coke intensity along the wavelength region was investigated and the results are shown in [Table 1-2].

According to the survey results, the correlation between calibration curves for three wavelength ranges is examined to calibrate the cold and hot strengths of coal. As a result, the 450-2,100 cm-¹ wavelength range is defined as the 2,100-4,000 cm-¹ range It appears to have a somewhat quantitative relationship.

However, using a wavelength range of 450-4,000 cm-¹ may yield more advantageous results than using a wavelength range. However, the wider the wavelength range, the more time it takes to prepare a calibration model.

However, selecting a highly correlated wavelength range is a way to increase the accuracy of the future calibration model for coal.

Table 1-2

                 Analysis wavelength range (cm-¹) Cold strength Hot strength 450-2,100 0.965 0.968 2,100-4,000 0.959 0.952 450-4,000 0.984 0.977

The second step of the present invention describes the measurement conditions of the infrared spectrometer and the construction and operation of the sample cup of the present invention, as shown in FIG.                     

The FTIR device is a Fourier transform infrared spectrometer and is a general-purpose device that has been mainly used for qualitative analysis of organic matters. To quantitatively analyze coal samples, it is important to find measurement conditions for obtaining good reproducible spectra.

In particular, in the case of solid powder samples such as coal, infrared spectra are obtained, and thus the reproducibility of the spectra depends on the measurement conditions and the shape of the sample cup.

Infrared spectra of coal by diffuse reflection did not yield a linear correlation between the absorption intensity of the spectra according to Beer's law and the concentration of the sample.

However, if diffuse reflection occurs under conditions where the size of the coal powder sample particles that are distributed is larger than the wavelength of incident light and much smaller than the thickness of the sample layer, the Kubelka-Munk function [f] (R∞)] was used to approximate a linear correlation between the sample concentration and the spectra obtained by reflection.

f (R∞) = (1- R∞) ² / 2 R∞ = K / S = (ln10) ac / S ======== Equation 1

Where a is the molar extinction coefficient in the light transmission spectroscopy, c is the concentration of the sample, K and S are the extinction coefficient and scattering coefficient of the sample in diffusion reflection spectroscopy, respectively, and R∞ is the diffuse reflectance at an infinite depth of the virtually set sample.

In addition, the spectrum is measured while changing the angle of incidence by giving an inclination to the sample cup in the form as shown in FIG. 3, and as a result, reproducibility of the sample can be ensured as shown in FIG. 4.                     

Details of the slope of the sample cup are shown in [Table 2-1].

The test method for verifying the reproducibility of the coal infrared spectrum according to the slope of the sample cup is compared with the energy value of the infrared spectrum measured three times at the slopes of five different conditions as shown in [Table 2-1] below.

Table 2-1

Test Slope (°) Energy values in the spectrum Remarks Measurement 1 Measurement 2 Measurement 3 Test 1 6 26,080 25,243 28,512 Bad Test 2 8 25,420 25,480 25,502 Good Test 3 10 24,852 24,826 24,862 Good Test 4 12 24,500 24,508 24,516 Good Test 5 14 21,520 23,216 22,548 Bad

The comparative test results of Table 2-1 show that the measured energy value of the sample is the best when the inclination of the sample cup is in the range of 8 ° to 12 ° of test 4 in the sample cup.

Based on these results, the numerical values of the sample cup inclination, the size of the sample injection hole, and the material of the sample cup are defined as follows.The holes into which the sample is inserted are made of five sample injection holes, such as 31a to 31e of FIG. In order to give an inclination angle, the height is produced as shown in 33, 34 of FIG.

Details of the sample cup of the present invention are as follows [Table 2-2].

Table 2-2

division standard Remarks Sample Cup Material and Size SUS310, L × H (50 × 6mm) Spectrum deformation due to surface wear during sample packing when using other Fe materials Slope of the surface 8 ~ 12 ° Minimize diffuse reflection Sample injection hole size Diameter 6 x height 2.2 mm 5 holes are available for continuous work

The third step of the present invention is to develop a highly correlated calibration model that enables coke characterization of coal samples using spectral information reproducibly measured in the infrared wavelength range of 450 to 4,000 cm −1.

Table 1

[Table 2]

And, based on the calibration model obtained from the coal standard sample of [Table 1] knowing the concentration, the method of estimating the concentration of unknown sample is used.

The calibration model refers to a calibration function mathematically implemented to be applied to calibration, and for calibration of a sample for which concentration is to be obtained, input necessary information to obtain a coefficient used to obtain a calibration function.

As a method for obtaining such coefficients, the present invention prepares a coal standard sample as shown in [Table 1], and carbonizes each sample and calculates the cold strength, reaction rate, and hot strength index of the coke according to the conventional analytical technology.                     

The concentration range of the standard sample used in the calibration model is considered to include the maximum and minimum concentrations of unknown samples to be analyzed in the future, and the volatile content (v%) has a range of 16v% to 42v%, and forms coal coke. The standard SPEC. Is determined by preparing 130 kinds of 40 types of coal to have a constant particle size (0.15mm or less) and concentration range (cold strength: 50.0 ~ 95.0).

Details of coal standard samples are shown in [Table 1].

Infrared spectrum measurement method of the coal standard sample is filled with a spoon into the sample charging holes (31b, 31c, 31d) of Figure 3 and gently press the sample surface smoothly so as not to scratch the sample loading space (Fig. 22), close the lid and measure in the order of sample loading holes 31b, 31c, 31d of the sample cup to obtain the infrared spectrum of the sample, and to change the sample measuring hole, use the sample guide 24 of FIG. Push it in.

In the infrared spectrometer, the measurement conditions of the infrared spectrum of the coal sample were as shown in [Table 3-1], but the number of scans and the purge time may be higher than the reference value, but the efficiency of the analysis time is inferior.

Table 3-1.

division Measuring conditions Definition of terms Scan count 128scan Improves signal to noise ratio (S / N ratio) Purge Time 4min Prevention of moisture and CO2 in the air Background Single measurement Blank test meaning as reference spectrum Sample Spectrum Abs measurement Absorption Spectrum Calculation

In order to obtain the correlation with the coking strength from the measured infrared spectrum of coal, it is possible to quantify the spectrum, and in particular, when the spectrum is matrixed, mathematically implemented linear algebraic principles can be applied. Can be processed.

As the numerical method of spectral information, correlation with concentration is investigated by using two mathematical calculation methods, Partial Least Square (PLS) and Principal Component Regression (PCR).

As a result, as shown in [Table 3-2], the calculation method of PLS is about 0.04 higher than that of PCR.

[Table 3-2] Correlation by PCR and PLS Calculation

Test Data processing method Cold strength Reaction rate Hot strength Exam 1 PCR 0.94 0.93 0.92 Exam 2 Pls 0.98 0.96 0.97

The reason for this is presumed that the concentration value of the coal sample is the value measured by the physical test, so that an error is contained in the concentration value.

In general, if there is an error in the concentration of the standard sample, the PLS calculation performs an abbreviation process that removes all the overlapping elements for the concentration matrix as well as the spectral matrix. There is a possibility that the error can be further reduced by adding.

However, it is known that the PCR calculation removes duplicate elements only in the spectral matrix, and thus does not find a problem due to an error by assuming that the value input to the concentration matrix is a true value.

According to the test results in Table 3-2, the coking strength of coal samples is measured using a physical measuring device, and the error caused by analysis implies that PLS is more effective than PCR.

The present invention will be described in more detail with reference to the following Examples.

Example 1

In order to implement a multivariate calibration model for the analysis of coal coke, infrared spectra of 42 kinds of 130 coals of [Table 1] were measured, and the measured spectra are shown in FIG. It is shown.

In order to make the particle size of the sample small and uniform by the method of pretreatment of the sample before the infrared spectrum measurement of coal, it was crushed to 0.15mm or less using a disk grind mill, and the crushed coal sample was dried for 1hr at 105 ℃ dryer and then wavelength range 450 Measure the infrared spectrum in the ˜4.000 cm − 1 region.

The measured spectral information was converted into the spectrum to which the Kubelka-Munk function was applied, and as shown in [Table 2], all data of all wavelength ranges (450 ~ 4.000 cm-¹) were digitized for 130 coal standard samples.

The quantized spectral information is excellent in correlation by inputting concentration values (DI 150, CRR, CSR) of each coal sample based on the PLS calculation method and performing statistical processing using a computer as shown in [Table 2]. A multivariate calibration model for coke characterization can be obtained.

The validity test results for the measured multivariate calibration model are shown in [Table 4-1] below.

Table 4-1

DI150 CRR CSR SEP 1.50 2.47 2.35 r 0.98 0.96 0.97 factors 9 7 9

SEP (standard Error of Prediction) Forecast error

r: correlation coefficient, closer to 1 is ideal

factors: The range of 5 to 10 is ideal when applying the calibration model.

The validity test of the completed calibration model is performed by the Leave One Out Cross Validation method.

The procedure of this method first removes one of the spectra of several samples used to obtain the calibration curve, then obtains the calibration curve with the remaining spectra, and then applies the removed spectrum to the newly obtained calibration curve and then calculates the expected and actual concentrations from that calibration curve. Find the error and repeat this process for several samples to find the average error and then check if the average error is within the allowable range.

In principle, the test should be applied to all samples used for calibration, but if there are many samples, it will take too much time to test. In general, several samples are selected for partial inspection. In the present invention, the allowable range is determined based on the allowable error of the sample concentration used for the calibration.

In the present invention, the tolerance standard is within 4% as in the conventional analytical method, and in order to obtain a high-efficiency calibration curve, it is important to select a suitable number of factors to obtain a high-correlation calibration curve. The number of factors should be equal to the number of compounds in the sample that can affect the spectrum.

In the present invention, the cold water strength is f = 9, the reaction rate is f = 7, and the hot strength is f = 9.

As a result of preparing the calibration model, the SEP value is 1.50 ~ 2.47%, which is lower than the error control standard 4%, and the correlation coefficient r value is 0.96 ~ 0.98, and the number of factors used is 7 ~ 9, which shows the effectiveness of the calibration model. .

Example 2

As shown in [Table 4-4], 27 samples of bituminous coal used for coke are randomly sampled and tested by the previous analysis method and infrared analysis method according to the present invention, and the coke cold strength, reaction rate, and hot strength are respectively classified and compared by each item. Conduct the analysis.

The measurement of the coal sample by the analytical method of the present invention is to put the sample in the hole No. 31b, 31c, 31d of the sample cup of Fig. 3 after finishing flat to avoid scratches on the surface of the coal sample 23 of Fig. After raising to the charging space, the infrared spectrum was measured under the measurement conditions shown in [Table 4-2].

 Table 4-2

division Measuring conditions Scan count 128scan Purge time 4min Background Single measurement Sample Spectrum Abs measurement

Spectral information of unknown coal samples was applied to the multivariate calibration model developed in Example 1. The test results are shown in [Table 4-3].

As a result of the comparative test, the analysis data according to the present invention shows that the average error compared to the analysis using the conventional physical measuring device is as follows [Table 4-3], the cold strength is 1.0%, the reaction rate 2.2%, the hot strength 2.6%. The error value is the present invention because the test result by the physical measuring device in the correlation method of the conventional analytical technique has the characteristic of the physical test that contains a lot of errors up to 2.9 to 5.9% as shown in the following [Table 4-3]. It can be seen that the analysis precision of is a good result.

Table 4-3

Comparing the Error of the Tube Method and the Infrared Method Test Cold strength Reaction rate Hot strength Customs law Infrared ray Customs law Infrared ray Customs law Infrared ray Mean error 2.9 1.0 4.6 2.2 5.9 2.6

Details of the tests in Table 4-3 are shown in Table 4-4 below.

Table 4-4

Comparison test between inertial measurement method and infrared method Sample classification Cold strength (DI 150) Response rate (CRR) Hot strength (CSR) Customs law Infrared ray Difference Customs law Infrared ray Difference Customs law Infrared ray Difference Sample 1 86.6 85.9 0.7 20.5 21.8 1.3 70.5 67.5 3.0 Sample 2 78.9 80.6 1.7 24.8 28.7 3.9 59.2 56.1 3.1 Sample 3 84.5 86.3 1.8 21.7 21.2 0.5 69.4 71.2 1.8 Sample 4 82.1 79.8 2.3 25.4 28.4 3.0 57.9 54.3 3.6 Sample 5 84.4 84.0 0.4 30.9 27.5 3.4 60.4 63.0 2.6 Sample 6 87.1 88.3 1.2 21.0 17.7 3.3 71.7 75.1 3.4 Sample 7 84.7 85.7 One 16.3 19.0 2.7 74.6 72.0 2.6 Sample 8 78.8 78.9 0.1 34.6 35.6 1.0 57.5 53.9 3.6 Sample 9 83.3 85.2 1.9 29.7 26.2 3.5 58.9 62.2 3.3 Sample 10 88.2 87.7 0.5 21.5 21.6 0.1 75.6 74.0 1.6 Sample 11 86.7 85.6 1.1 21.0 21.3 0.3 65.4 68.0 2.6 Sample 12 84.6 84.9 0.3 26.9 28.2 1.3 62.3 59.7 2.6 Sample 13 78.3 77.6 0.7 35.0 38.4 3.4 53.8 50.2 3.6 Sample 14 81.6 80.9 0.7 24.7 27.8 3.1 58.0 56.5 1.5 Sample 15 84.7 82.9 1.8 26.8 25.6 1.2 64.2 60.7 3.5 Sample 16 84.5 85.6 1.1 30.7 28.0 2.7 59.8 61.7 1.9 Sample 17 87.8 87.5 0.3 19.0 20.0 1.0 72.4 69.5 2.9 Sample 18 85.3 84.9 0.4 23.3 25.1 1.8 70.1 66.3 3.8 Sample 19 86.4 86.3 0.1 20.0 21.6 1.6 71.8 69.0 2.8 Sample 20 70.8 69.1 1.7 51.8 50.2 1.6 31.3 28.9 2.4 Sample 21 84.2 85.8 1.6 27.5 25.3 2.2 66.5 69.9 3.4 Sample 22 85.0 86.0 One 27.4 26.3 1.1 57.6 59.4 1.8 Sample 23 84.2 85.0 0.8 31.1 28.0 3.1 60.2 62.6 2.4 Sample 24 86.6 86.0 0.6 35.5 32.6 2.9 49.7 50.7 1.0 Sample 25 85.0 85.9 0.9 23.5 20.3 3.2 63.9 61.8 2.1 Sample 26 87.3 85.9 1.4 18.3 21.0 2.7 72.9 74.5 1.6 Sample 27 86.7 85.0 1.7 33.5 30.9 2.6 59.2 57.5 1.7 Average 84.0 84.0 1.0 26.8 26.6 2.2 62.8 62.1 2.6

As shown in the examples, the present invention can be applied to the coke cold strength (DI150) and the reaction rate (CRR) hot strength (CSR) of coal samples by simply applying infrared spectrum information of coal to the developed multivariate calibration model for the coke characterization. It is possible to obtain the physical properties.

The mean error value according to the present invention refers to the physical test measurement of the conventional analytical technique as a true value, and indicates a difference in the analytical value according to the present invention.

However, the conventional analytical technique includes an error in the analytical data by a physical measurement test, and the f test method of Table 4-5 examined the significance of the present invention in the 95% confidence interval.

The f-test method is widely used as a test method used to test data of conventional and new methods.

Table 4-5

Average Standard Deviation Coefficient of variation f0 Standard method 84.0 1.100 1.3094 0.8633 change 84.0 1.060 1.2624 Σxi2 190924.25 Σxi) 2 / n 190562.40 SA 361.85      V1 13.92 COUNTN 27 Σxi2 190813.55 Σxi) 2 / n 190394.42 SB 419.13 V2 16.12 COUNTN 27 95% confidence interval f (2.98) Criteria Good (no significant difference) f> f0 Poor (significant) f <f0

The results show that there is no significant difference in the 95% confidence interval, indicating that the analysis technique is comparable to the conventional analysis technique.

The analytical technique of the present invention will be effective in determining the coking characteristics of coal by testing the present invention in a consistent steel mill and coal producing region where coal should be made of high strength coke.

According to the test results of the present invention, the most preferred application of infrared spectroscopy of coal is to use the sample cup of FIG. 3 which can measure the coal powder sample reproducibly, and to test 130 coal standard samples composed of 42 carbon species of [Table 1]. After drying at high temperature under the same conditions (1250 ℃, 19hr) by the tube method, test coke was obtained, and the coke cold strength (DI 150) and the reaction rate (CRR), which were physical measurement tests, were measured on all samples. The standard value is set.

In addition, the correlation between the infrared spectrum information of the sample and the concentration of the sample measured by the tube method is applied to the PLS statistical processing method to implement a calibration model having a high correlation coefficient.

As described above, the method for analyzing the coking characteristics of coal by the non-drying method according to the present invention is a multi-coal calibration using FTIR, which is a relatively simple equipment for analyzing cold strength, reaction rate and hot strength among the coke characteristics of coal. By developing a model and enabling coke characterization, it is possible to estimate the coking characteristics in a simple way without coking coal, and also to measure the coking coal's cold strength, reaction rate and hot strength. The complete elimination of equipment and physical measuring devices has the potential to save a lot of time and effort.

Claims (1)

Measuring the spectrum of the coal sample with an infrared wavelength range of 450 to 4000 cm-¹ and a tilt of the sample cup containing the coal sample as 8 to 12 °; Converting the spectrum such that the absorption intensity of the measured spectrum has a linear correlation with the concentration of the coal sample; Quantifying the spectral information to obtain a correlation with coking characteristics from the transformed spectrum; A method of analyzing coking characteristics of coal by a non-drying method of analyzing the cold strength, reaction rate, and hot strength of the coke comprising the step of implementing a calibration model for performing the coking characteristics by statistically processing the quantized spectral information.

Images