阅读说明：本技术 粉率测定方法及装置 (Powder rate measuring method and device ) 是由 坪井俊树 山平尚史 于 2020-04-03 设计创作，主要内容包括：本发明能实时且高精度地测定附着在块状物质表面的粉的比例(粉率)。具有如下步骤：测定距离测定装置与块状物质间的距离的步骤S1、从由该步骤S1得到的距离数据算出特征量的步骤S2、以及将由该步骤S2算出的特征量变换为粉率的步骤S3；由步骤S2算出的特征量表示从步骤S1得到的距离数据算出的距离变动。如果块状物质的粉率提高,则在块状物质表面高度方向上,因三维形状内的微小凹凸所造成的微小的距离变动会变大,因而通过将其设为特征量,能实时且高精度地测定块状物质的粉率。(The present invention can measure the proportion (powder rate) of powder attached to the surface of a massive material in real time and with high accuracy. Comprises the following steps: a step S1 of measuring the distance between the distance measuring device and the bulk material, a step S2 of calculating the characteristic amount from the distance data obtained in the step S1, and a step S3 of converting the characteristic amount calculated in the step S2 into a powder ratio; the feature value calculated in step S2 represents the distance variation calculated from the distance data obtained in step S1. If the powder rate of the bulk material is increased, the minute distance variation due to the minute irregularities in the three-dimensional shape in the height direction of the surface of the bulk material becomes large, and thus the powder rate of the bulk material can be measured in real time with high accuracy by using this as a characteristic amount.)

1. A method for measuring a powder ratio, comprising:

step S1, measuring the distance between the distance measuring device and the block-shaped material x;

step S2 of calculating a feature amount from the distance data obtained in step S1; and

in step S3, the feature quantity calculated in step S2 is converted into a powder rate.

2. The powder fraction measuring method according to claim 1, wherein the feature quantity calculated in step S2 represents a distance variation calculated from the distance data obtained in step S1.

3. The powder ratio measuring method according to claim 2, wherein the feature amount calculated at step S2 is based on a standard deviation value in a standard deviation matrix obtained by applying a standard deviation filter to the distance data obtained at step S1.

4. The flour fraction measuring method according to claim 3, wherein the feature amount calculated in step S2 is based on a mode of a standard deviation value in a standard deviation matrix obtained by applying a standard deviation filter to the distance data obtained in step S1.

5. The powder fraction measuring method according to claim 3 or 4, wherein the filter processing range of the standard deviation filter is 10 x 10 pixels or less.

6. A powder ratio measuring method according to any one of claims 1 to 5, wherein in step S1, a distance to the bulk material x is measured by a distance measuring device provided above the bulk material x.

7. A powder ratio measuring device is provided with:

a distance measuring device (1) for measuring the distance to the block-shaped material (x); and

the calculation device (2) is provided with a calculation means (2a) for calculating a characteristic amount from the distance data obtained by the distance measurement device (1), and a conversion mechanism (2b) for converting the characteristic amount calculated by the calculation means (2a) into a powder ratio.

8. The powder fraction measuring apparatus according to claim 7, wherein the calculating means (2a) calculates a characteristic amount indicating a distance variation from the distance data obtained by the distance measuring apparatus (1).

9. The powder ratio measuring apparatus according to claim 8, wherein the calculating means (2a) applies a standard deviation filter to the distance data obtained by the distance measuring apparatus (1) and calculates the characteristic amount from a standard deviation value in the obtained standard deviation matrix.

10. The powder ratio measuring apparatus according to claim 9, wherein the calculating means (2a) applies a standard deviation filter to the distance data obtained by the distance measuring apparatus (1) and calculates a mode of a standard deviation value in the obtained standard deviation matrix as the feature amount.

11. The powder fraction measuring apparatus according to claim 9 or 10, wherein the standard deviation filter has a filter processing range of 10 x 10 pixels or less.

12. The powder ratio measuring apparatus according to any one of claims 7 to 11, wherein the distance measuring device (1) is provided above the bulk material x, and measures the distance to the bulk material x.

Technical Field

The present invention relates to a powder ratio measuring technique for measuring a powder ratio (powder ratio) adhering to the surface of a lump of ore, coke, or the like, which is a blast furnace raw material.

Background

In a production process using a raw material such as a mineral, the particle size distribution of the raw material must be measured in advance because the particle size distribution of the raw material affects the operation of the production process. In particular, in order to ensure the gas flow in the blast furnace, it is important to grasp the particle size distribution of the raw material such as ore and coke, and it is necessary to perform the operation while paying attention to the ratio of powder (for example, particle size of 5mm or less) adhering to relatively large particles (lumps) in the raw material.

In the conventional blast furnace operation, in order to grasp the particle size distribution of the raw material, periodic sampling of the raw material and particle size measurement by a sieve are performed, but this method has a problem that it takes time to analyze. Patent document 1 discloses a technique for increasing the analysis frequency by automating the sampling of the raw material, but if the sampling frequency is excessively increased, there is a risk of delaying the operation process, and the sampling is typically problematic because of the sampling inspection.

As a conventional technique for sampling a raw material and measuring the particle size by a sieve as described above, a technique for measuring the particle size of a raw material during transportation in real time using a camera or the like has been proposed.

For example, patent document 2 discloses a method in which raw material bulk transported by a conveyor is imaged on the conveyor to create image data, a luminance distribution is obtained from the image data, and the particle size of the raw material bulk is detected using the maximum peak height of the luminance distribution.

Further, patent document 3 discloses a method of detecting the moisture content of the contents from the spectral information obtained from the reflected light in the near infrared region among the reflected light from the contents charged into the blast furnace, and detecting the content powder rate in real time based on the relationship between the moisture content of the contents and the powder rate of the powder adhering to the contents, which is grasped in advance.

Patent document 4 discloses a method of obtaining an average luminance of image data of a captured bulk material as a feature amount, and obtaining a powder ratio (powder ratio) of the surface of the bulk material from the feature amount.

Documents of the prior art

Patent document

Patent document 1 Japanese patent application laid-open No. 2005-134301

Patent document 2 Japanese laid-open patent application No. 2000-329683

Patent document 3 Japanese patent laid-open publication No. 2015-124436

Patent document 4 International publication No. 2018/101287

Disclosure of Invention

However, the above-described conventional techniques have the following problems.

First, the method of patent document 2 is limited by the analysis capability of the camera, and it is not possible to sufficiently ensure the measurement accuracy including the adhering powder around the bulk material.

In addition, the method of patent document 3 does not necessarily have a high correlation between the moisture content of the contents and the powder fraction, and therefore the measurement accuracy is insufficient.

In addition, the method of patent document 4 is not always highly correlated with the luminance and the pink ratio of the camera image, and thus the measurement accuracy is insufficient, as in patent document 3.

Accordingly, an object of the present invention is to solve the above-described problems of the prior art, and to provide a powder rate measuring method and device capable of measuring the rate of powder adhering to the surface of a cake-like material (powder rate) in real time and with high accuracy (high accuracycacy).

The present inventors have made extensive studies to find a novel powder ratio measuring technique capable of solving the above problems. As a result, it has been found that the distance to the bulk material as the object to be measured for the powder ratio is measured by the distance meter, the characteristic amount relating to the powder ratio is obtained from the measured distance data, and the characteristic amount is converted into the powder ratio, whereby the ratio of the powder adhering to the surface of the bulk material (powder ratio) can be measured in real time with high accuracy.

The present invention has been completed based on such findings, and the gist thereof is as follows.

[1] A method for measuring a powder ratio, comprising: a step (S1) for measuring the distance between the measuring device and the block material (x);

a step (S2) of calculating a feature value from the distance data obtained in the step (S1); and

and a step (S3) for converting the characteristic amount calculated in the step (S2) into a powder ratio.

[2] The powder ratio measuring method according to [1], wherein the feature quantity calculated in the step (S2) represents a distance variation calculated from the distance data obtained in the step (S1).

[3] The powder ratio measuring method according to [2], wherein the feature amount calculated in step (S2) is based on a standard deviation value in a standard deviation matrix obtained by applying a standard deviation filter to the distance data obtained in step (S1).

[4] The method for measuring a powder fraction according to [3], wherein the feature amount calculated in step (S2) is based on a mode of a standard deviation value in a standard deviation matrix obtained by applying a standard deviation filter to the distance data obtained in step (S1).

[5] The method for measuring a powder ratio according to the above [3] or [4], wherein a filter processing range of the standard deviation filter is 10 × 10 pixels or less.

[6] The powder ratio measuring method according to any one of the above [1] to [5], wherein in the step (S1), a distance to the bulk material (x) is measured by a distance measuring device provided above the bulk material (x).

[7] A powder ratio measuring device is provided with: a distance measuring device (1) for measuring the distance from the bulk material (x); and

the calculation device (2) is provided with a calculation means (2a) for calculating a characteristic amount from the distance data obtained by the distance measurement device (1), and a conversion means (2b) for converting the characteristic amount calculated by the calculation means (2a) into a powder ratio.

[8] The powder fraction measuring apparatus according to the above [7], wherein the calculating means (2a) calculates a characteristic amount indicating a distance variation from the distance data obtained by the distance measuring apparatus (1).

[9] The powder ratio measuring apparatus according to the above [8], wherein the calculating means (2a) applies a standard deviation filter to the distance data obtained by the distance measuring apparatus (1) and calculates the feature amount from a standard deviation value in the obtained standard deviation matrix.

[10] The powder fraction measuring apparatus according to the above [9], wherein the calculating means (2a) applies a standard deviation filter to the distance data obtained by the distance measuring apparatus (1) and calculates a mode of a standard deviation value in the obtained standard deviation matrix as the feature amount.

[11] The powder ratio measuring apparatus according to the above [9] or [10], wherein a filter processing range of the standard deviation filter is 10 × 10 pixels or less.

[12] The powder ratio measuring apparatus according to any one of the above [7] to [11], wherein the distance measuring device (1) is provided above the massive material (x) and measures the distance to the massive material (x).

According to the present invention, the ratio of powder adhering to the surface of the bulk material (powder ratio) can be measured in real time with high accuracy. Therefore, for example, the powder ratio (coke powder ratio) of the blast furnace coke can be reliably determined before charging into the blast furnace, and this contributes to stabilization of the blast furnace operation.

Drawings

FIG. 1 is an explanatory view showing an embodiment of the present invention applied to the measurement of the coke powder rate before charging into a blast furnace.

Fig. 2 is an example of a three-dimensional coke shape image based on the distance obtained by the distance measuring device in the embodiment of fig. 1.

Fig. 3 is an explanatory diagram showing an example of a calculation method for calculating a standard deviation matrix of distance data by applying a standard deviation filter to the distance data when calculating a feature amount from the distance data obtained by the distance measuring device in the present invention.

Fig. 4 is a graph showing a distribution of standard deviation values of the standard deviation matrix calculated by the calculation of fig. 3.

Fig. 5 is a diagram of a case where, when a standard deviation filter having a filter processing range of 3 × 3 matrix (3 × 3 pixels) is applied to the distance data of the image of fig. 2, a standard deviation value of 0.5 is set as a threshold value in an output 800 × 1000 standard deviation matrix, and binarization is performed with white and black.

Fig. 6 is a schematic view of an impression of overlapping coke particles (blocks).

FIG. 7 is a graph showing the correlation between the characteristic amount obtained by the present invention and a known powder ratio, wherein the characteristic amount is an average value of standard deviation values in a standard deviation matrix.

Fig. 8 is a graph showing a correlation between the characteristic amount obtained by the present invention and a known powder ratio, and the characteristic amount is a mode of a standard deviation value in a standard deviation matrix.

FIG. 9 is a flow chart of one embodiment of the present invention.

Detailed Description

The powder ratio measuring method of the present invention is a method for measuring the powder ratio of a bulk material x based on the amount of powder adhering to the surface of the bulk material x, and comprises the steps of: a step S1 of measuring the distance to the bulk material x with a distance measuring device, a step S2 of calculating the characteristic amount from the distance data obtained in the step S1, and a step S3 of converting the characteristic amount calculated in the step S2 into the powder rate.

Further, the present invention provides a powder ratio measuring apparatus for carrying out the powder ratio measuring method, comprising: a distance measuring device 1 for measuring the distance to the block material x; and a calculation device 2 having a calculation means 2a and a conversion means 2b, wherein the calculation means 2a calculates a characteristic amount from the distance data based on the distance obtained by the distance measurement device 1, and the conversion means 2b converts the characteristic amount calculated by the calculation means 2a into a powder ratio.

In the present invention, examples of the bulk material x to be measured for powder fraction include: the lump material (ore, coke, etc.) used in a metal refining process such as an iron making process is not limited thereto.

Here, the powder ratio is a ratio of the mass of powder having a predetermined size or less to the total mass of the bulk material x having powder adhered to the surface thereof.

Hereinafter, an embodiment of the present invention will be described by taking a case where the lump material x as the powder ratio measuring object is coke before charging into a blast furnace as an example.

FIG. 1 shows an embodiment of the present invention, and shows a case where the present invention is applied to the measurement of the coke powder ratio before charging into a blast furnace. In the figure, the symbol 3 is a hopper, the symbol 4 is a sieve, the symbol 5 is a conveyor, and the symbol x_cCoke is an object to be measured for powder content. The reference numeral 1 denotes a distance measuring device constituting the powder ratio measuring device of the present invention, and the reference numeral 2 denotes a calculating device in the same manner. The arithmetic unit 2 includes: a calculation means 2a for calculating a feature amount from the distance data obtained by the distance measurement device 1; and a conversion means 2b for converting the characteristic amount calculated by the calculation means 2a into a powder ratio.

Coke x charged into blast furnace_cStored in a hopper 3, and discharged from the hopper 3 as coke x_cThe fine powder is sieved out by the sieve 4, and then transferred to the conveyor 5, and conveyed by the conveyor 5 to the blast furnace (a hopper at the top of the furnace). The coke x carried by the conveyor 5_cCoke particles (lumps) on the screen of the screen 4 and attached powder (coke powder) which is not screened by the screen 4 due to the attachment of the coke particles and the like.

In the present embodiment, the coke x conveyed by the conveyor 5 is used_cFor this purpose, the ratio of powder mainly composed of the adhering powder (powder ratio) was measured as follows.

First, the coke x on the conveyor 5 is measured by the distance measuring device 1 provided above the conveyor 5_cThe distance to obtain coke x_cThe three-dimensional shape data (step S1). As the distance measuring device 1, for example, a two-dimensional laser range finder can be used.

When this laser range finder is used, the coke x is measured for each 1 line by irradiating the laser beam in the width direction of the conveyor_cThe distance to this point. Here, 1 line corresponds to the width of the laser beam irradiated in the width direction of the conveyor. Due to coke x_cThe coke x is linearly measured by the laser distance measuring instrument at a predetermined measurement cycle by being transported and moved by the conveyor 5_cThe measured values of these lines are connected in sequence to obtain coke x_cThe three-dimensional shape data of (1). The above method is a method of obtaining a three-dimensional shape of a measurement object by a so-called optical sectioning method, and a laser distance meter and a data processing means used therefor may be conventionally used.

The laser distance measuring instrument preferably has a measuring area having the same width as the conveyor, and can measure the coke x conveyed by the conveyor 5_cOverall (full face). In addition, the shorter the measurement period, the better, especially preferably 1kHz or more. In the present embodiment, a measurement period of 4kHz is set.

The distance measuring device 1 may be a distance measuring device other than the two-dimensional laser range finder, and may be a distance measuring device configured by a stereo method using two cameras, for example.

FIG. 2 is a coke x based on distance obtained by a two-dimensional laser rangefinder_cThree-dimensional shape image of (overlooking coke x on conveyor 5 from above)_cImages of (b) is used. In fig. 2, the white gray scale indicates that the height is higher and the distance to the distance meter is shorter. In this image, the horizontal direction is 800 pixels in the width direction of the conveyor, the vertical direction is 1000 pixels in the forward direction of the conveyor, and the size of 1 pixel is 2mm × 4mm in the horizontal direction. Further, the distance is obtained for each pixel.

That is, fig. 2 is a graph in which data of a distance in the conveyor width direction (hereinafter referred to as "distance data") of 800 pixels for 1 line is connected by 1000 lines. Thus, distance data of 800 pixels × 1000 pixels is obtained. The resolution in the height direction was 5 μm.

Here, in the conventional technique of performing image processing of three-dimensional shape data, generally, signal processing is performed from three-dimensional shape data including the coke unevenness, thereby performing separation processing on individual coke particles. The particle size distribution is calculated by counting the number of particles of the coke whose particle size has been separated by the particle separation process and making a histogram.

In this case, for example, if the minimum analysis capability in the vertical and horizontal directions of the distance measuring device 1 is 4mm × 2mm and the analysis capability in the height direction is 5 μm, the particle diameter of coke charged into the blast furnace is generally 35mm or more, and therefore, the analysis capability is sufficient for the measurement of the particle diameter of coke particles (lumps) by signal processing. However, the adhering powder (coke powder) adhering to the surface of the coke particles (lumps) often contains adhering powder having a particle size of 1mm or less. If the attached powder is spherical, the distance measuring apparatus 1 has a sufficiently high analysis capability in the height direction, but has an insufficient analysis capability in the vertical and horizontal directions. Therefore, it is difficult to count the number of particles of the adhering powder as coke particles (lumps) and determine the powder ratio.

On the other hand, if the resolution in the vertical and horizontal directions is improved by making the distance measuring device as close to the coke as possible and narrowing the measurement range width by the distance measuring device, the powder adhered to the coke surface can be grasped and the powder ratio can be measured. However, if the distance measuring device is close to the coke, only a very small portion of the adhering powder of the coke can be grasped, and the powder rate of the whole coke (the whole conveyor width) conveyed by the conveyor cannot be obtained. However, in this case, there are problems such as complexity of data processing, large restrictions in installation, and increased cost.

In contrast, the present invention includes the entire conveyor width in the measurement region, and can measure the powder ratio with high accuracy even when the resolution in the vertical and horizontal directions is insufficient. That is, in the present invention, coke x is measured_cThe distance to the coke x is obtained by obtaining a characteristic quantity indicating a minute distance fluctuation from the distance data and converting the characteristic quantity into a powder fraction_cThe ratio of the powder attached to the surface (powder ratio).

In the present invention, as described above, the characteristic amount indicating a minute distance fluctuation is calculated from the distance data (three-dimensional shape data of coke) measured by the distance measuring device 1 (step S2). The distance data obtained by the distance measuring device 1 is insufficient in the longitudinal and lateral directions for powder ratio measurement, but is sufficient in the height direction, and is sufficient even when the entire conveyor width is included in the measurement region.

The present inventors have found that if the amount of powder adhering to the coke surface increases, that is, the powder fraction increases, the fine irregularities in the three-dimensional shape in the coke surface height direction, that is, the fine distance variation in the coke height direction increases. Therefore, the present invention uses such a small distance variation as a feature amount, and obtains the powder ratio from the feature amount.

In the present embodiment, it is assumed that a minute distance variation is a local variation of a certain height, and a standard deviation filter (a filter for calculating a standard deviation) having a small filter processing range is applied to the distance data to derive a feature amount from the obtained standard deviation value. That is, the larger the fine unevenness on the coke surface due to the high dust ratio, the larger the standard deviation value obtained by applying the standard deviation filter, and therefore, the feature amount is derived from this standard deviation value.

First, the obtained distance data is divided into pixels. In the case of the distance data of fig. 2, it is 800 × 1000 pixels. Next, the respective distances corresponding to the respective pixels are applied to produce an 800 × 1000 matrix. Then, a general standard deviation filter of a 3 × 3 matrix (corresponding to 3 × 3 pixels) in the filter processing range is applied to the distance data of the 800 × 1000 matrix, a standard deviation value is obtained for each 3 × 3 matrix, and a feature amount is derived from the standard deviation value.

Fig. 3 shows an example of a calculation method (calculation chart) when the standard deviation filter is applied to the distance data. In fig. 3, symbol 6 is a standard deviation filter, and symbol 7 is a standard deviation matrix for 4 × 4 output. This example shows a case where the standard deviation filter 6 having a filter processing range of 3 × 3 matrix is applied to distance data of 4 × 4 matrix (corresponding to 4 × 4 pixels). Fig. 3(a) is an impression diagram of the standard deviation filter 6 in which a 3 × 3 matrix is applied to a 4 × 4 matrix for input, and fig. 3(B) is an impression diagram in which calculated values are stored in a 4 × 4 matrix for output. The standard deviation matrix for output of fig. 3(B) is created from the matrix for input of fig. 3 (a). The numbers in fig. 3(a) and 3(B) are examples for explanation.

Specific steps are described below.

First, a 4 × 4 output matrix 7 is prepared, and all 0(zero) are stored. As shown in fig. 3(a), the standard deviation of 9 pixels in total is calculated in the target filter range, and the calculated standard deviation value is input to the position of the output matrix 7 corresponding to the center position in the filter range. Moving to the next adjacent range, the same process is repeated. In this way, in the example of fig. 3, a total of 4 times of filter calculations are performed for one input by using a 4 × 4 matrix.

In the case of the distance data of fig. 2, such calculation is applied to the distance data of the 800 × 1000 matrix, thereby outputting a standard deviation matrix of the 800 × 1000 distance data, and the feature value is obtained using the standard deviation matrix of the 800 × 1000.

In order to capture a small variation, the standard deviation filter 6 preferably has a small filter processing range (number of pixels), and is therefore preferably 10 × 10 pixels or less (or 100 pixels or less in total), and more preferably 5 × 5 pixels or less (or 25 pixels or less in total). Among them, 3 × 3 pixels (or 9 pixels in total) are particularly preferable, and 2 × 2 pixels are most preferable. The reason for this is as follows: if the processing range of the filter is small, the filter is less likely to be affected by the shape of the coke itself, the inclination of the coke measuring surface with respect to the distance measuring device, and the like.

Fig. 4 is a distribution diagram showing the standard deviation values of the standard deviation matrix to which the above-described sequence is applied to the distance data of fig. 2, in which the peak of the standard deviation value shown by symbol 8 indicates the mode of the standard deviation value. In this example, the standard deviation values in the standard deviation matrix are divided into a sufficiently large number of steps (5 ten thousand (0.00002 interval) in this example), and the standard deviation value having the highest frequency in the steps is set as a mode. With the exception of frequencies with a standard deviation of 0 (zero).

Fig. 5 is a diagram of a case where, in 800 × 1000 standard deviation matrices output when a standard deviation filter of a 3 × 3 matrix (3 × 3 pixels) of a filter processing range is applied to the distance data shown in fig. 2, binarization is performed with white (standard deviation value of 0.5 or more) and black (standard deviation value of less than 0.5) using 0.5 standard deviation value as a threshold value. As is clear from a comparison between fig. 5 and fig. 2, the matrix elements storing the values having the standard deviation of 0.5 or more are mostly located at the height difference and boundary of the overlapped cokes (symbol 9 in fig. 5).

Fig. 6 is a schematic diagram showing an impression of overlapped coke particles (blocks). In the figure, reference numeral 10 denotes a coke overlapped. Reference numeral 11 denotes a case where a standard deviation filter is applied to the surface of coke, and reference numeral 12 denotes a case where a standard deviation filter is applied to the height difference boundary of overlapped cokes. As described above, in the standard deviation matrix obtained from the distance data, there are a large number of values calculated for the overlapped coke level difference or boundary, and the standard deviation value is very large.

In the present invention, the standard deviation value representing a slight variation due to the adhering powder adhering to the coke surface should be included in the feature amount, and therefore, it is preferable to exclude the standard deviation value affected by the level difference, the boundary, and the like of the overlapped cokes. The mean standard deviation value in the standard deviation matrix (for example, 800 × 1000 standard deviation matrices) contains noise due to the influence of the level difference and the boundary of the overlapped cokes, but if the mode 8 of the standard deviation value in the standard deviation matrix shown in fig. 4 is sufficiently large, the noise is hardly influenced by the level difference and the boundary of the overlapped cokes. Therefore, although the average value of the standard deviation values in the standard deviation matrix may be used as the feature value, it is preferable to use the mode 8 of the standard deviation values in the standard deviation matrix as shown in fig. 4 as the feature value.

In the present embodiment, a method using a standard deviation filter is applied to the feature value calculation representing a minute distance variation, but the method is not limited to this, and a method using a high frequency component of a two-dimensional fourier transform may be applied, for example, considering an 800 × 1000 matrix image.

Next, the feature amount obtained as described above is converted into a powder ratio (step S3). The conversion is performed using a coefficient (relational expression) obtained in advance based on the correlation between the feature amount and the known powder ratio.

Fig. 7 and 8 show the correlation between the characteristic amount and the known powder ratio. Here, fig. 7 uses the average value of the standard deviation values in the standard deviation matrix as the feature amount, and fig. 8 uses the mode of the standard deviation values in the standard deviation matrix as the feature amount. Here, FIGS. 7 and 8 show the results obtained by using, as a lump material, a lump coke having a particle size of 35mm or more having a coke powder having a particle size of 1mm or less adhered to the surface thereof. In FIGS. 7 and 8, the vertical axis represents the powder fraction (mass%) of coke powder of 1mm or less adhering to the coke, and the horizontal axis represents the characteristic amount of minute fluctuation calculated from the distance data obtained by measuring the coke powder of 1mm or less adhering to the coke.

The coke lumps having a particle size of 35mm or more to be subjected to the test were prepared by sieving the coke with a sieve having 35mm openings. More than 100 coke blocks are used. The powder fraction of coke powder having a particle size of 1mm or less deposited on the surface of the lump coke is calculated as the mass ratio (percentage) of the mass difference of the lump coke before and after sieving to the mass difference before and after sieving by drying the lump coke at 120 to 200 ℃ for 4 hours or more until the lump coke becomes a constant amount and sieving the dried lump coke with a sieve having an opening of 1 mm. This method utilizes a method in which the adhering powder is peeled off in a dry state.

In either case of fig. 7 and 8, the characteristic amount and the powder ratio have a clear correlation. However, in the case of the average value of the standard deviation values in the standard deviation matrix shown in fig. 7, the correlation coefficient is R0.60, and the measurement error (root mean square error) σ is 0.23, whereas in the case of the mode of the standard deviation values in the standard deviation matrix shown in fig. 8, the correlation coefficient is R0.70, the measurement error σ is 0.20, and the mode of the standard deviation values in the standard deviation matrix shows a better correlation. Therefore, when there are many differences in height and boundaries between the overlapped cokes, it is desirable to use the mode of the standard deviation value in the standard deviation matrix. When the above-described characteristic amount is linearly regressed with a known powder ratio, the slope a and the y-intercept b are shown as "a" 4.89 and "b" 2.16 in fig. 7, and as "a" 35.6 and "b" 1.6 in fig. 8. Here, linear regression is performed, but multiple regression and nonlinear regression may be performed.

In the present invention, a coefficient (relational expression) is obtained in advance based on the correlation between the feature amount (preferably, the mode of the standard deviation in the standard deviation matrix) and the known power ratio as shown in fig. 7 and 8, and the feature amount (preferably, the mode of the standard deviation in the standard deviation matrix) is converted into the power ratio using the coefficient. Thus, the coke powder ratio can be measured with high measurement accuracy (for example, with a measurement error σ of 0.3 or less).

Fig. 9 is a flowchart of one embodiment of the present invention described above. In the present embodiment, as described above, the coefficient (relational expression) for converting the feature amount into the powder ratio is obtained in advance from the correlation between the feature amount and the known powder ratio.

The distance measuring device 1 measures the lump material x (for example, the coke x conveyed by a conveyor) as the object to be measured for the powder ratio_c) Distance data (three-dimensional shape data) is acquired (step S1). Next, the calculation means 2a of the calculation device 2 applies the distance data to a standard deviation filter to obtain a standard deviation value, and calculates the mode of the standard deviation value in the standard deviation matrix to use it as a feature value (step S2). Next, the conversion means 2b of the operation device 2 converts the characteristic amount into a powder ratio using the known coefficient (relational expression) to determine the ratio of the powder adhering to the bulk material x (powder ratio) (step S3).

Then, the above-mentioned step S1 is performed at predetermined measurement intervals, and each time the distance data is obtained in step S1, the steps S2 and S3 are performed to obtain the powder yield.

Thus, the powder rate of the bulk material x can be measured in real time with high accuracy.

The above embodiment is to use the present invention for the coke x charged in front of the blast furnace_cThe present invention is not limited to the above measurement, and can be applied to the measurement of the powder ratio of various lump materials x.

Further, the present invention is suitable for a method of measuring the powder rate of the lump material x (coke, ore, etc.) being transported by a conveyor or the like in real time, but even if the object is the lump material x in a stationary state, the method can be applied to the powder rate measurement of the lump material x in a stationary state by moving the distance measuring device 1 and measuring the three-dimensional shape.

In the above description, the size of the adhering powder is set to 1mm or less, but the size is not limited thereto and can be determined as appropriate. Even when the adhering powder has a size other than 1mm or less, for example, 2mm or less, the powder ratio can be measured by obtaining the correlation between the characteristic amount and the powder ratio in advance.

Description of the reference numerals

1 distance measuring device

2 calculation device

2a computing mechanism

2b conversion mechanism

3 hopper

4 sifter

5 conveyor

6 standard deviation filter

7 matrix for output

Mode of 8 standard deviation

9 difference in height/boundary between overlapped cokes

10 overlapping coke

11 schematic drawing of standard deviation filter applied to coke surface

12 schematic of a level difference/boundary standard deviation filter for coke