JP7704703B2 - Particle size measuring device, method and program thereof, and granulating device and method thereof - Google Patents

Description

The present invention relates to a particle size measuring device, a particle size measuring method, and a particle size measuring program for measuring particle size, as well as a granulation device and a granulation method for granulating granular material, which are equipped with these.

Measurement of particle size, such as particle size (particle diameter) and particle size distribution (particle size distribution), is required in various fields that handle particulate raw materials and products, for example, for setting manufacturing conditions and quality evaluation. In one example, iron ore pellets, which are the raw material charged into a blast furnace, are produced by adding auxiliary materials and binders as necessary to the fine ore, which is the raw material for the pellets, and then adding a predetermined amount of water to granulate raw pellets using a granulator, which are then dried and fired. It is known that the particle size of the raw pellets fluctuates during the granulation stage of the raw pellets due to fluctuations in granulation conditions such as the particle size, supply amount, and added water amount of the raw pellets, and changes in the generation status of deposits inside the granulator. On the other hand, the raw material charged into a blast furnace is required to have a uniform pellet diameter in order to ensure ventilation inside the blast furnace. Therefore, the particle size of the raw pellets granulated by the granulator is measured. This method of measuring particle size is disclosed, for example, in Patent Document 1.

The method for measuring the average particle size of granular material disclosed in Patent Document 1 is a method for measuring the average particle size of accumulated granular material, in which the average particle size of the granular material is determined using at least one of the nth moment Mn (n = 0, 1, 2, ...) of the power spectrum of an image of the accumulated granular material. In one embodiment, a particle extraction image is generated by binarizing or floating binarizing the image of the accumulated granular material, and the nth moment Mn of the power spectrum of this particle extraction image is used. The floating binarization is performed by taking a moving average of the image to generate a blurred image, generating an image by subtracting the blurred image from the image, and binarizing the subtracted image.

Japanese Patent Publication No. 6-75030 (Japanese Patent Publication No. 2-264845)

However, in the method for measuring the average particle size of granular materials disclosed in Patent Document 1, when an image contains a mixture of individual microparticles and microparticles attached to or deposited on large particles, the power spectrum of the image treats them in the same way, resulting in a decrease in the accuracy of the particle size. The threshold value used in the binarization or floating binarization causes the contours of particles to be buried in noise in the same image, resulting in a decrease in the accuracy of the particle size. In the floating binarization, the blurred image is subtracted from the image, so fine particles are buried, resulting in a decrease in the accuracy of the particle size.

The present invention has been made in consideration of the above circumstances, and its purpose is to provide a particle size measuring device, a particle size measuring method, and a particle size measuring program that can measure particle size with greater accuracy. The present invention also provides a granulation device equipped with the particle size measuring device, and a granulation method equipped with the particle size measuring method.

As a result of various studies, the inventor of the present invention found that the above object can be achieved by the present invention described below. That is, the particle size measuring device according to one aspect of the present invention includes an image acquisition unit that acquires an image of the granular substance of the measurement target, a statistical feature amount processing unit that acquires a statistical feature amount based on the relationship between each pixel value of a first pixel and a second pixel within a predetermined range of the first pixel from the image of the measurement target acquired by the image acquisition unit, a correspondence relationship information storage unit that stores correspondence relationship information representing the correspondence relationship between the statistical feature amount and particle size, and a particle size processing unit that acquires a particle size corresponding to the statistical feature amount acquired by the statistical feature amount processing unit using the correspondence relationship information stored in the correspondence relationship information storage unit. Preferably, in the above-mentioned particle size measuring device, the particle size processing unit further acquires a particle size distribution (particle size distribution) in the image of the measurement target. Preferably, in the above-mentioned particle size measuring device, the image acquisition unit is an imaging device that captures the granular substance of the measurement target to generate an image of the measurement target. Preferably, in the above-mentioned particle size measuring device, the image acquisition unit is an interface circuit that inputs and outputs data with an external device, and the external device is a storage medium that stores an image of the measurement target. Preferably, in the above-mentioned particle size measuring device, the image acquisition unit is an interface circuit that inputs and outputs data with an external device, and the external device is a drive device that reads data from a recording medium that records an image of the measurement target. Preferably, in the above-mentioned particle size measuring device, the image acquisition unit is a communication interface circuit that transmits and receives communication signals with an external device, and the external device is a server device that is connected to the communication interface circuit via a network and manages the images of the measurement target.

Such a particle size measuring device obtains statistical features based on the relationship between the pixel values of the first and second pixels from the image of the object to be measured, and converts them into particle size (particle diameter), allowing for more accurate measurement of particle size.

In another aspect, in the particle size measuring device described above, the statistical feature processing unit divides the image of the measurement target into a plurality of regions and obtains each statistical feature for each of the plurality of regions. Preferably, in the particle size measuring device described above, the plurality of regions are each a mesh obtained by dividing the image of the measurement target into a mesh pattern.

Such particle size measuring devices obtain statistical features of an area and convert them into particle size, so the particle size to be detected can be selected by adjusting the size (area) of the area. This makes it possible to more accurately measure the proportion of free-standing fine particulate matter when a mixture of free-standing fine particulate matter and fine particulate matter attached to or stacked on large-sized particulate matter is captured in the image of the measurement target.

In another aspect, in the above-mentioned particle size measuring device, the statistical feature processing unit obtains a co-occurrence matrix in the image of the measurement target acquired by the image acquisition unit, and obtains a correlation value between rows and columns in the obtained co-occurrence matrix as the statistical feature. Preferably, in the above-mentioned particle size measuring device, the co-occurrence matrix is a matrix that represents, for each pixel value, the probability of occurrence of an adjacent pixel pair in which the relationship between the first pixel value of the pixel (target pixel, reference pixel) and the second pixel value of the adjacent pixel adjacent to the pixel is the same. Preferably, in the above-mentioned particle size measuring device, the co-occurrence matrix is a matrix that represents, for each pixel value, the probability of occurrence of an adjacent pixel pair in which the relationship between the first pixel value of the pixel (target pixel, reference pixel) and the second pixel value of the adjacent pixel adjacent to the pixel on the right side in the row direction is the same.

By using a co-occurrence matrix, such a particle size measuring device can determine statistical features through simple information processing (simple calculation processing).

In another aspect, in the above-mentioned particle size measuring device, the predetermined range is a range adjacent to the first pixel. Preferably, in the above-mentioned particle size measuring device, the first and second pixels are two pixels adjacent to each other. Preferably, in the above-mentioned particle size measuring device, the predetermined range is a range adjacent to the first pixel on one side (right side) or the other side (left side) of the horizontal direction (row direction) of the image. Preferably, in the above-mentioned particle size measuring device, the predetermined range is a range adjacent to the first pixel on one side (upper side) or the other side (lower side) of the vertical direction (column direction) of the image. Preferably, in the above-mentioned particle size measuring device, the predetermined range is a range to the first pixel in the first diagonal direction (upper right direction), second diagonal direction (upper left direction), third diagonal direction (lower right direction), or fourth diagonal direction (lower left direction).

This makes it possible to provide a particle size measuring device in which the specified range is a range adjacent to the first pixel.

In another aspect, the particle size measuring device described above further includes an illumination unit that illuminates the granular material to be measured.

Since such a particle size measuring device further includes an illumination unit, it is possible to measure particle size under a constant lighting environment, thereby reducing variation in measurement accuracy.

A particle size measurement method according to another aspect of the present invention includes an image acquisition step of acquiring an image of the measurement target obtained by capturing an image of the granular substance of the measurement target, a statistical feature processing step of determining, from the image of the measurement target acquired in the image acquisition step, a statistical feature based on the relationship between pixel values of a first pixel and a second pixel that is within a predetermined range of the first pixel, and a particle size processing step of determining a particle size corresponding to the statistical feature determined in the statistical feature processing step, using correspondence information that indicates the correspondence between the statistical feature and particle size.

A particle size measurement program according to another aspect of the present invention is a program that causes a computer to execute an image acquisition process for acquiring an image of a measurement target obtained by capturing an image of the measurement target granular material, a statistical feature amount processing process for determining, from the image of the measurement target acquired in the image acquisition process, a statistical feature amount based on the relationship between pixel values of a first pixel and a second pixel that is within a predetermined range of the first pixel, and a particle size processing process for determining a particle size corresponding to the statistical feature amount determined in the statistical feature amount processing process, using correspondence information that indicates the correspondence between the statistical feature amount and particle size.

This particle size measurement method and program obtains statistical features based on the relationship between pixel values of adjacent pixels from the image of the object to be measured, and converts them into particle size (particle diameter), allowing for more accurate measurement of particle size.

A granulation device according to another aspect of the present invention includes a granulation section that granulates a granular material from a raw material under predetermined granulation conditions, any one of the above-mentioned particle size measuring devices that measures the particle size of the granular material granulated in the granulation section, and an adjustment section that adjusts the predetermined granulation conditions based on the particle size of the granular material determined by the particle size measuring device.

This provides a granulation device equipped with any of the above-mentioned particle size measuring devices. The granulation device adjusts the specified granulation conditions, so that it can granulate granular material with a specified particle size as a target.

In another aspect, in the above-mentioned granulation device, the granular material is raw pellets of granulated iron ore produced by adding quicklime as a binder to the raw material fine ore and adding a predetermined amount of water, and the adjustment unit adjusts at least one of the mixing ratio when the fine ore contains multiple types, the amount of quicklime added, and the predetermined amount of water.

This type of granulation device can granulate iron ore to a specified particle size.

A granulation method according to another aspect of the present invention includes a granulation step in which a granular material is granulated from a raw material under predetermined granulation conditions, the above-mentioned particle size measurement method in which the granular material granulated in the granulation step is used as the measurement object to determine the particle size of the granular material, and an adjustment step in which the predetermined granulation conditions are adjusted based on the particle size of the granular material determined by the particle size measurement method.

This provides a granulation method that includes the above-mentioned particle size measurement method. The above-mentioned granulation method adjusts the specified granulation conditions, so that granular material can be granulated to a specified particle size.

The particle size measuring device, particle size measuring method, and particle size measuring program of the present invention can measure particle size with greater accuracy. The present invention also provides a granulation device equipped with the particle size measuring device and a granulation method equipped with the particle size measuring method.

1 is a block diagram showing a configuration of a particle size measuring device in a first embodiment. FIG. FIG. 2 is a diagram for explaining the case where the particle size measuring device is used in a granulation process as an example. FIG. 13 is a diagram for explaining a method of calculating a gray level co-occurrence matrix for the first row. FIG. 13 is a diagram for explaining a method of calculating a gray level co-occurrence matrix for the first row. FIG. 13 is a diagram for explaining a method of calculating a gray level co-occurrence matrix for the second to sixth rows. FIG. 13 is a diagram for explaining a gray level co-occurrence matrix obtained as a result of calculation, as an example. FIG. 11 is a diagram for explaining a gray level co-occurrence matrix obtained as a result of calculation as another example. 11 is a diagram for explaining correlation values between rows and columns in a co-occurrence matrix for an image of a measurement target. FIG. FIG. 11 is a diagram for explaining a method for calculating a statistical feature amount. 4 is a flowchart showing the operation of the particle size measuring device. FIG. 4 is a diagram showing the correlation between actual measurement results and the measurement results of the particle size measuring device. FIG. 2 is a diagram for explaining a measurement result of a specific example using the particle size measuring device. FIG. 11 is a schematic diagram showing the configuration of a granulation system in a second embodiment. FIG. 2 is a schematic diagram of a drum mixer in the granulation device of the granulation system. FIG. 2 is a block diagram showing the electrical configuration of a granulation control device in the granulation system. 4 is a flowchart showing the operation of a granulation control device regarding adjustment of granulation conditions.

One or more embodiments of the present invention will be described below with reference to the drawings. However, the scope of the invention is not limited to the disclosed embodiments. Note that components with the same reference numerals in each drawing are the same components, and their description will be omitted as appropriate. In this specification, when referring to a general term, a reference numeral without a subscript is used, and when referring to an individual component, a reference numeral with a subscript is used.

The particle size measuring device in the embodiment is a device for measuring particle sizes such as particle size (particle diameter) and particle size distribution (particle diameter distribution) of a granular material to be measured. This particle size measuring device includes an image acquisition unit that acquires an image of the granular material to be measured, a statistical feature amount processing unit that obtains a statistical feature amount based on the relationship between each pixel value of a first pixel and a second pixel within a predetermined range of the first pixel from the image of the object to be measured acquired by the image acquisition unit, a correspondence information storage unit that stores correspondence information representing the correspondence between the statistical feature amount and particle size, and a particle size processing unit that obtains a particle size corresponding to the statistical feature amount obtained by the statistical feature amount processing unit using the correspondence information stored in the correspondence information storage unit. Hereinafter, such a particle size measuring device will be described using an example applied to a granulation process in the manufacture of iron ore pellets and sintered ore for blast furnaces as an example, but the granular material is not limited to granulated materials during the manufacture of iron ore pellets and sintered ore, and may be any material (e.g. raw materials, products, etc.) as long as it is granular (particulate).

1 is a block diagram showing the configuration of a particle size measuring device in the first embodiment. FIG. 2 is a diagram for explaining, as an example, the case where the particle size measuring device is used in a granulation process. FIG. 2A is a schematic diagram showing the whole, and FIG. 2B is a schematic diagram showing the image acquisition unit. FIG. 3 is a diagram for explaining a method of calculating a gray level co-occurrence matrix for the first row. FIGS. 3A and 3C show each pixel value of an image, and FIGS. 3B and 3C show a co-occurrence matrix. FIG. 4 is a diagram for explaining a method of calculating a gray level co-occurrence matrix for the first row. FIGS. 4A and 4C show each pixel value of an image, and FIGS. 4B and 4C show a co-occurrence matrix. FIG. 5 is a diagram for explaining a method of calculating a gray level co-occurrence matrix for the second to sixth rows. FIGS. 5A and 5C show each pixel value of an image, and FIGS. 5B and 5C show a co-occurrence matrix. FIG. 6 is a diagram for explaining, as an example, a gray level co-occurrence matrix of the calculation result. FIG. 6A shows each pixel value of an image, FIG. 6B shows a co-occurrence matrix, and FIG. 6C shows a heat map of the co-occurrence matrix. FIG. 7 is a diagram for explaining a gray level co-occurrence matrix of the calculation result as another example. FIG. 7A shows each pixel value of an image, FIG. 7B shows a co-occurrence matrix, and FIG. 7C shows a heat map of the co-occurrence matrix. FIG. 8 is a diagram for explaining the correlation value between rows and columns in the co-occurrence matrix for the image to be measured. FIG. 8A shows the correlation value, and FIG. 8B to FIG. 8E show each sample image of sample image numbers 1 to 4. The horizontal axis of FIG. 8A is the sample image number, and the vertical axis is the correlation value (COR). FIG. 9 is a diagram for explaining a method of calculating statistical features. FIG. 9A shows an image, FIG. 9B shows statistical features for each region, and FIG. 9C shows a histogram of each statistical feature.

The particle size measuring device D in the first embodiment includes, for example, an image acquisition unit 1, a control processing unit 2, a memory unit 3, an input unit 4, an output unit 5, and an interface unit (IF) 6, as shown in FIG. 1.

The image acquisition unit 1 is connected to the control processing unit 2 and is a device that acquires an image of the measurement target by capturing an image of the granular material of the measurement target under the control of the control processing unit 2. The image acquisition unit 1 is, for example, an imaging device that captures an image of the granular material of the measurement target to generate an image of the measurement target. The imaging device is, for example, a color digital camera or a monochrome digital camera. Alternatively, the image acquisition unit 1 is, for example, an interface circuit that inputs and outputs data to and from an external device. The external device is, for example, a storage medium such as a USB (Universal Serial Bus) memory or an SD card (registered trademark) that stores an image of the measurement target. Alternatively, the external device is a drive device that reads data from a recording medium, such as a CD-ROM (Compact Disc Read Only Memory), a CD-R (Compact Disc Recordable), a DVD-ROM (Digital Versatile Disc Read Only Memory), or a DVD-R (Digital Versatile Disc Recordable), on which an image of the measurement target is recorded. The interface circuit as the image acquisition unit 1 may be connected to the external device by wire or wirelessly. Alternatively, the image acquisition unit 1 may be, for example, a communication interface circuit that transmits and receives communication signals to and from an external device, and the external device is a server device that is connected to the communication interface circuit via a network (WAN (Wide Area Network, including a public communication network)) or LAN (Local Area Network) and manages images of the measurement target. Note that, when the image acquisition unit 1 is an interface circuit or a communication interface circuit, the image acquisition unit 1 may also be used as the IF unit 6 (i.e., the IF unit 6 may be used as the image acquisition unit 1).

In this embodiment, the particle size measuring device D is used, for example, in the granulation process of a blast furnace, and in order to measure the particle size of iron ore pellets in approximately real time, the image acquisition unit 1 is a color digital camera (hereinafter abbreviated as "camera") 1. Note that the image acquisition unit 1 may also be a monochrome digital camera.

In the granulation process of iron ore pellets for blast furnaces, for example, as shown in FIG. 2A, two pan-type granulators P-1 and P-2 are installed in parallel as granulators. Each granulator P-1 and P-2 is supplied with raw material for granulation, which is made by mixing powdered ore with auxiliary materials such as limestone and binders such as bentonite as necessary, and adding a predetermined amount of moisture. The raw material for granulation is granulated into pellets by rotating each granulator P-1 and P-2 at a predetermined inclination angle and rotation speed. The raw pellets (granulated pellets) Ob discharged from each granulator P-1 and P-2 are discharged by conveyors B-1 and B-2, respectively, and then merged on a collecting conveyor B-3. From this conveyor B-3, the pellets are sieved to a predetermined grain size width via a vibrating sieve (not shown), and then transported to a calciner such as a grate kiln (not shown) for drying and calcination.

In a plant implementing such a granulation process, the image acquisition unit 1 of the particle size measuring device D includes, for example, a camera 1a (1a-1, 1a-2) arranged to capture an image of the granulated pellets (an example of a granular material) Ob conveyed on the transport conveyors B-1, B-2 from above, more specifically, from directly above as shown in Figures 2A and 2B. In the example shown in Figure 2, the image acquisition unit 1 includes not only the camera 1a, but also a pair of illumination devices 1b (1b-1, 1b-2), 1c (1c-1, c-2) arranged side by side via the camera 1a in a direction perpendicular to the transport direction of the transport conveyors B-1, B-2 to illuminate the granulated pellets Ob from diagonally above. A pair of illumination devices 1b and 1c are provided on the left and right sides of the camera 1a to intentionally illuminate the granulated pellets Ob so as to generate a shadow of the granulated pellets Ob with a brightness that changes the brightness depending on the presence or absence of the granulated pellets Ob on the conveyor B, thereby making it possible to stably display a change in brightness in the granulated pellets Ob to be measured. Therefore, the particle size measuring device D can measure the particle size under such a constant illumination environment, so that the variation in measurement accuracy can be reduced. There are two sets (two sets) of the camera 1a and the pair of illumination devices 1b and 1c as the image acquisition unit 1 corresponding to the two conveyors B-1 and B-2, and the first set of the camera 1a-1 and the pair of illumination devices 1b-1 and 1c-1 is provided for the conveyor B-1, and the second set of the camera 1a-2 and the pair of illumination devices 1b-2 and 1c-2 is provided for the conveyor B-2. The set of camera 1a and the pair of lighting devices 1b, 1c are arranged in the same manner with respect to the transport conveyor B, so FIG. 2B mainly illustrates the first set of camera 1a-1 and the pair of lighting devices 1b-1, 1c-1 arranged with respect to the transport conveyor B-1, and the second set of camera 1a-2 and the pair of lighting devices 1b-2, 1c-2 arranged with respect to the transport conveyor B-2 is illustrated by listing the reference numbers of camera 1a-2 and the pair of lighting devices 1b-2, 1c-2 in parentheses after the reference numbers of camera 1a-1 and the pair of lighting devices 1b-1, 1c-1 corresponding to camera 1a-2 and the pair of lighting devices 1b-2, 1c-2, respectively.

The input unit 4 is connected to the control processing unit 2 and is a device that inputs various commands, such as a command to start measuring the particle size of the measurement target by the particle size measuring device D, and various data required for operating the particle size measuring device D, such as the date of measurement, to the particle size measuring device D, and is, for example, a plurality of input switches assigned with predetermined functions, a keyboard, a mouse, etc. The output unit 5 is connected to the control processing unit 2 and is a device that outputs commands and data input from the input unit 4 and particle sizes measured by the particle size measuring device D under the control of the control processing unit 2, and is, for example, a display device such as a CRT display, LCD (liquid crystal display device), or organic EL display, or a printing device such as a printer, etc.

The input unit 4 and the output unit 5 may be configured as a touch panel. In the case of configuring this touch panel, the input unit 4 is a position input device that detects and inputs an operation position, for example, a resistive film type or a capacitive type, and the output unit 5 is a display device. In this touch panel, a position input device is provided on the display surface of the display device, and one or more input content candidates that can be input to the display device are displayed. When a user touches the display position that displays the input content that the user wants to input, the position is detected by the position input device, and the display content displayed at the detected position is input to the particle size measuring device D as the user's operation input content. With such a touch panel, the user can easily intuitively understand the input operation, and a particle size measuring device D that is easy for the user to handle is provided.

The IF unit 6 is connected to the control processing unit 2 and is a circuit that inputs and outputs data to and from, for example, an external device according to the control of the control processing unit 2, such as an interface circuit for RS-232C, which is a serial communication method, an interface circuit using the Bluetooth (registered trademark) standard, and an interface circuit using the USB standard. The IF unit 6 may also be a communication interface circuit that transmits and receives communication signals to and from an external device, such as a data communication card or a communication interface circuit conforming to the IEEE 802.11 standard.

The storage unit 3 is connected to the control processing unit 2 and is a circuit that stores various predetermined programs and various predetermined data under the control of the control processing unit 2. The various predetermined programs include, for example, a control program that controls each unit 1, 3 to 6 of the particle size measuring device D, a statistical feature amount processing program that obtains a statistical feature amount based on the relationship between each pixel value of a first pixel and a second pixel that is within a predetermined range relative to the first pixel from an image of the measurement target obtained by the image acquisition unit 1, and a particle size processing program that obtains a particle size corresponding to the statistical feature amount obtained by the statistical feature amount processing program using correspondence information stored in the correspondence information storage unit 31 described later. The various predetermined data include data necessary for executing each of these programs, such as the image of the measurement target obtained by the image acquisition unit 1 and the correspondence information. Such a storage unit 3 includes, for example, a ROM (Read Only Memory) which is a non-volatile storage element, and an EEPROM (Electrically Erasable Programmable Read Only Memory) which is a rewritable non-volatile storage element. The storage unit 3 also includes a RAM (Random Access Memory) which serves as a working memory for the control processing unit 2 and stores data generated during the execution of the specified program. The storage unit 3 may also be configured with a hard disk device with a relatively large storage capacity.

The storage unit 3 functionally includes a correspondence information storage unit 31 that stores the correspondence information. The correspondence information is information that represents the correspondence between the statistical feature amount and the particle size of the granular substance. More specifically, the correspondence information is information that represents the correspondence between the correlation value and the particle size of the granular substance, with the statistical feature amount being the correlation value between a row and a column in a co-occurrence matrix of the image of the object to be measured. The correspondence information is, for example, created in advance from a plurality of samples and stored in the correspondence information storage unit 31. The correlation value functions as an index for evaluating the particle size of the granular substance Ob.

The control processing unit 2 is a circuit that controls each of the units 1, 3 to 6 of the particle size measuring device D according to the function of each unit, and measures the particle size of the granular material to be measured. The control processing unit 2 is configured, for example, with a CPU (Central Processing Unit) and its peripheral circuits. By executing a control processing program, the control processing unit 2 functionally comprises a control unit 21, a statistical feature processing unit 22, and a particle size processing unit 23.

The control unit 21 controls each of the parts 1, 3 to 6 of the particle size measuring device D according to the function of each part, and is responsible for the overall control of the particle size measuring device D.

The statistical feature processing unit 22 obtains statistical features based on the relationship between pixel values of a first pixel and a second pixel that is within a predetermined range of the first pixel from the image of the measurement target obtained by the image acquisition unit 1. More specifically, the statistical feature processing unit 22 obtains a co-occurrence matrix for the image of the measurement target obtained by the image acquisition unit, and obtains the correlation value between rows and columns in the obtained co-occurrence matrix as the statistical feature.

The particle size processing unit 23 obtains the particle size corresponding to the statistical feature obtained by the statistical feature processing unit 22 using the correspondence information stored in the correspondence information storage unit 31. In this embodiment, the particle size processing unit 23 further obtains the particle size distribution (particle size distribution) in the image of the measurement object. The particle size distribution (particle size distribution) is a histogram showing the number of particles of each particle size in the plurality of particles captured in the image of the measurement object. More specifically, the particle size processing unit 23 obtains the particle size corresponding to the correlation value obtained by the statistical feature processing unit 22 using the correspondence information stored in the correspondence information storage unit 31, and obtains the particle size histogram by obtaining the frequency of occurrence for each particle size class. Alternatively, the particle size processing unit 23 obtains a histogram of the correlation value by obtaining the frequency of occurrence for each correlation value class for the correlation value obtained by the statistical feature processing unit 22, and converts the correlation value class into particle size using the correspondence information stored in the correspondence information storage unit 31 to obtain the particle size distribution in the image of the measurement object.

Here, the statistical feature and the relationship between this statistical feature and particle size will be described. When the granular material Ob is illuminated so as to generate the shadow of the granular material Ob with a brightness that causes a change in luminance depending on the presence or absence of the granular material Ob, in an image obtained by converting a color image to, for example, a 256-level grayscale (an image in which RGB pixel values are converted to luminance values using a known conversion formula), the pixel value of the pixel in which the granular material Ob is reflected becomes a pixel value close to the brightest luminance value of 255, while the pixel value of the pixel in which the shadow is reflected becomes the darkest black luminance value of 0. Therefore, as the particle size of the granular material Ob becomes smaller, the frequency (probability) of alternating between pixels with a luminance value of 0 due to the shadow and pixels with a luminance value close to luminance value 255 irradiated by the granular material Ob increases. Therefore, when there is a high probability that a pixel having a luminance value similar to that of a pixel of interest (pixel of interest) appears in the vicinity of the pixel of interest, the particle size of the granular substance Ob can be estimated to be large, whereas when there is a high probability that a pixel having a luminance value different from that of the pixel of interest appears in the vicinity of the pixel of interest, the particle size of the granular substance Ob can be estimated to be small. Thus, for example, the particle size of the granular substance Ob can be estimated by the probability distribution of luminance values appearing in pixels neighboring a pixel of a certain luminance value (0 to 255). For this reason, the statistical feature amount is an amount (value) based on the relationship between pixel values of a first pixel and a second pixel within a predetermined range relative to the first pixel, and is, for example, the difference in pixel values between neighboring pixels in the image to be measured, the ratio of pixel values between neighboring pixels, the similarity based on the difference or the ratio, the dissimilarity based on the difference or the ratio, the periodicity of the difference or the ratio, or the probability distribution of the difference or the ratio. The predetermined range is appropriately set from a plurality of samples within a range in which the statistical feature amount and the particle size of the granular material Ob are correlated. For example, the predetermined range is a range adjacent to the first pixel. That is, the first and second pixels are two pixels adjacent to each other. In one example, the predetermined range is a range adjacent to the first pixel on one side (right side) or the other side (left side) of the horizontal direction (row direction) of the image. The minimum distance between the first and second pixels is one pixel, and the maximum distance is the number of pixels corresponding to the minimum particle size of the particle size to be measured as the maximum diameter within the particle when viewed on a two-dimensional image. In another example, the predetermined range is a range adjacent to the first pixel on one side (upper side) or the other side (lower side) of the vertical direction (column direction) of the image. In another example, the predetermined range is a range to the first pixel in the first diagonal direction (upper right direction), second diagonal direction (upper left direction), third diagonal direction (lower right direction), or fourth diagonal direction (lower left direction).

For example, such a statistical feature, when it is a probability distribution of luminance values between neighboring pixels, can be obtained by a gray level co-occurrence matrix (GLCM) filter that extracts information about the texture of the image (spatial distribution pattern of pixel values). This GLCM filter calculates the frequency (probability) of a specific pair of cell values occurring at adjacent positions (e.g., the cell to the right, the cell above, or adjacent in all directions) at each position of the filter window. In other words, the GLCM filter is a matrix (co-occurrence matrix) whose elements are the probability Pδ(α, β) that the density of a point in the image that is a displacement δ (distance r, direction θ) away from a point (in one example, a pixel) with density α (in one example, a luminance value) is β.

More specifically, for example, in the case of an image with 256 gradations in Figs. 3 to 6, the GLCM is a matrix with 256 rows and 256 columns, with each element having a value between 0 and 1. The value of each row represents the pixel value (in this example, a luminance value between 0 and 255) of the pixel of interest (reference pixel), and each column represents the pixel value (in this example, a luminance value between 0 and 255) of the pixel adjacent to the pixel of interest (adjacent pixel) on the right side of the pixel of interest in the row direction. For example, in the case of a 6x6 image with smoothly changing pixel values (in this example, a luminance value between 0 and 255) as shown in Figs. 3A and 3C, the frequency (total number) of pairs in which the pixel of interest has a pixel value of 0 and the pixel value of the adjacent pixel is 0 does not exist in the image shown in Fig. 3A, and is therefore 0, so that the element in row 1 and column 1 of the GLCM expressed by frequency (frequency GLCM) is 0, as shown in Fig. 3B. In the image shown in Fig. 3A etc., there is one frequency (total number) of a pair in which the pixel of interest has a pixel value of 0 and the adjacent pixel has a pixel value of 1, as shown in Fig. 3C, so the element in row 1, column 2 of the frequency GLCM is 1, as shown in Fig. 3D. In the image shown in Fig. 3A etc., there is no frequency (total number) of a pair in which the pixel of interest has a pixel value of 0 and the adjacent pixel has a pixel value of 2, as shown in Fig. 4A, so the element in row 1, column 3 of the frequency GLCM is 0, as shown in Fig. 4B. Similarly, the frequency (total number) of a pair in which the pixel of interest has a pixel value of 0 and the adjacent pixel has a pixel value of k becomes the element in row 1, column k+1 of the frequency GLCM (k=0 to 255), and each element in the first row of the frequency GLCM is obtained, as shown in Fig. 4D. The frequency (total number) of pairs in which the pixel value of the pixel of interest is 1 and the pixel value of the adjacent pixel is k is the element in row 2 and column k+1 of the frequency GLCM, and each element in the second row of the frequency GLCM is obtained as shown in Fig. 5B. For example, the frequency (total number) of pairs in which the pixel value of the pixel of interest is 1 and the pixel value of the adjacent pixel is 2 is two in the image shown in Fig. 3A etc., as shown in Fig. 5A, so the element in row 2 and column 3 of the frequency GLCM is 2 as shown in Fig. 5B. Similarly, each element of the frequency GLCM is obtained up to the sixth row, as shown in Fig. 5D. For example, the frequency (total number) of pairs in which the pixel value of the pixel of interest is 4 and the pixel value of the adjacent pixel is 5 is five in the image shown in Fig. 3A etc., as shown in Fig. 5C, so the element in row 5 and column 6 of the frequency GLCM is 5 as shown in Fig. 5D. In this way, the frequency (total number) of pairs in which the pixel of interest has a pixel value of m and the adjacent pixel has a pixel value of n becomes the element of the frequency GLCM in m+1 rows and n+1 columns (m=0 to 255, n=0 to 255), and the frequency GLCM for the image shown in Figure 3A, Figure 6A, etc. becomes as shown in Figure 6B, and its heat map becomes as shown in Figure 6C. The GLCM is then calculated by dividing each element of the frequency GLCM by the total number of pixels in the image to calculate the probability of each element. The total number of images is, if the image has a size of M rows and N columns (total number of pixels M x N) and the neighboring pixels are K pixels away from the pixel of interest, as in the example above, when the neighboring pixels are adjacent to the pixel of interest in the row direction (left and right direction), the total number of pixels is M x (N-K); when the neighboring pixels are adjacent to the pixel of interest in the column direction (up and down direction), the total number of pixels is (M-K) x N; or when the neighboring pixels are adjacent to the pixel of interest in the diagonal direction, the total number of pixels is (M-K) x (N-K).

In the examples shown in Figures 3 to 6, the co-occurrence matrix is a matrix that represents, for each pixel value, the probability of occurrence of adjacent pixel pairs in which the relationship between the first pixel value of the pixel (pixel of interest, reference pixel) and the second pixel value of the adjacent pixel adjacent to the pixel on the right side in the row direction is the same.

For a 6x6 image with smoothly varying pixel values (in this example, luminance values from 0 to 255) that contain noise, as shown in Figure 7A, the frequency GLCM is as shown in Figure 7B, and the heat map is as shown in Figure 7C.

Once the co-occurrence matrix for the image of the object to be measured is obtained, the particle size can be estimated based on the probability distribution. In this embodiment, the correlation value of the pixel values (in this example, luminance values) of neighboring pixels with respect to the pixel of interest is normalized in the range of -1 to +1 and obtained. More specifically, from the co-occurrence matrix for the image of the object to be measured obtained as described above, the correlation value COR between the rows and columns in the co-occurrence matrix is obtained as the statistical feature amount using the following equation 1. Here, i is the luminance value of the pixel of interest, j is the luminance value of the neighboring pixel, and Pσ(i, j) is the value (occurrence probability) of the element in row i and column j in the co-occurrence matrix.

As shown in Figure 8A, this correlation value is +1 for the uniform image of sample image number 1 shown in Figure 8B, and has a profile that approaches -1 as the frequency of changes in brightness values between adjacent images increases, as in the images of sample image numbers 2 to 4 shown in Figures 8C to 8E.

In this embodiment, since the particle sizes of the multiple granular substances Ob captured in the image of the measurement target are rarely uniform, the statistical feature amount processing unit 22 divides the image PC of the measurement target into multiple areas AR (AR11 to AR45) as shown in FIG. 9A, and obtains each statistical feature amount for each of the multiple areas AR as shown in FIG. 9B. In FIG. 9B, the numerical values written in the squares in each area AR are correlation values as the statistical feature amount. In the example shown in FIG. 9A, the image PC is divided into 20 areas AR11 to AR15, AR21 to AR25, AR31 to AR35, and AR41 to AR45, which are 4×5 in size. In this example, the multiple areas AR are rectangular meshes that divide the image PC of the measurement target into a mesh shape (mesh shape). The shape of the mesh is not limited to a rectangle, and may be another shape such as a regular hexagon to divide the image PC in a honeycomb shape. It is preferable to set the size of the area AR to the maximum value within the particle size range to be detected.

For example, as shown in FIG. 9C, the granularity processing unit 23 obtains a histogram of correlation values by calculating the frequency of occurrence for each correlation value class for the correlation value COR obtained by the statistical feature amount processing unit 22, and converts the correlation value classes into particle sizes using the correspondence information stored in the correspondence information storage unit 31 to obtain a particle size distribution in the image of the measurement target. In the example shown in FIG. 9C, there are five classes: 0 to 0.1 (0 or more and less than 0.1), 0.2 to 0.3 (0.2 or more and less than 0.3), 0.3 to 0.4 (0.3 or more and less than 0.4), 0.4 to 0.5 (0.4 or more and less than 0.5), and 0.5 to 1 (0.5 or more and less than 1).

The control processing unit 2, memory unit 3, input unit 4, output unit 5, and IF unit 6 can be configured, for example, by a desktop or notebook computer. The computers that make up each of these units 2 to 6 are placed, for example, in an operation room in a granulation process plant and may be incorporated into a console (or may serve as the console), or may be separate from the console.

Next, the operation of this embodiment will be described. FIG. 10 is a flow chart showing the operation of the particle size measuring device. FIG. 11 is a diagram showing the correlation between the actual measurement results and the measurement results of the particle size measuring device. The horizontal axis of FIG. 11 is the powder rate actually measured using a sieve, expressed in mass%, and the vertical axis is the powder rate, expressed in mass%, determined by the particle size measuring device D. FIG. 12 is a diagram for explaining the measurement results of one specific example using the particle size measuring device. FIG. 12A shows an example of an image of the measurement target, and FIG. 12B shows the particle size determined by the particle size measuring device D for the image shown in FIG. 12A.

When the power is turned on, the particle size measuring device D configured as described above initializes each required part and starts its operation. In the control processing unit 2, a control unit 21, a statistical feature processing unit 22, and a particle size processing unit 23 are functionally configured by executing the control processing program.

In FIG. 10, first, the particle size measuring device D acquires an image of the measurement object using the image acquisition unit 1, and stores this acquired image in the memory unit 3 (S1).

Next, the particle size measuring device D divides the image into a plurality of regions by the statistical feature processing unit 22 of the control processing unit 2 (S2). The size of the regions is appropriately set in advance and stored in the storage unit 3 via the input unit 4. As described above, the size of the regions is set to the maximum value of the particle size range to be detected.

Next, the particle size measuring device D determines a statistical feature for each region by the statistical feature processing unit 22 (S3). In this embodiment, a correlation value COR is determined as the statistical feature for each region.

Next, the particle size measuring device D determines the particle size for each region using the particle size processing unit 23 of the control processing unit 2 (S4).

Next, the particle size measuring device D determines the particle size distribution (particle diameter distribution) in the image of the measurement object by the particle size processing unit 23 of the control processing unit 2 (S5).

In addition, instead of the above-mentioned processes S4 and S5, the particle size processing unit 23 may obtain a histogram of the correlation values by calculating the frequency of occurrence for each class of correlation values for the correlation value COR obtained by the statistical feature processing unit 22, and convert the classes of correlation values into particle sizes using the correspondence information stored in the correspondence information storage unit 31 to obtain the particle size distribution in the image of the object to be measured.

Next, the particle size measuring device D outputs the particle size determined in the process S4 and the particle size distribution determined in the process S5 to the output unit 5 by the control processing unit 2 (S6), and ends this process. Note that, if necessary, the particle size and particle size distribution may be output from the IF unit 6 to an external device.

In addition, in the granulation process, each of the steps S1 to S6 may be repeatedly performed at a predetermined time interval.

An example of the correlation between the powder fraction [mass %] of a granular material determined by such a particle size measuring device D and the powder fraction [mass %] of a granular material actually measured by a sieve is shown in FIG. 11. As shown in FIG. 11, the powder fraction [mass %] of a granular material determined by the particle size measuring device D correlates with the powder fraction [mass %] of a granular material actually measured by a sieve, and it can be seen from FIG. 11 that the particle size measuring device D in this embodiment can measure particle size and particle size distribution with high accuracy.

Figure 12B shows an example of particle size determined by particle size measuring device D for each of multiple regions. Figure 12B shows the particle size determined by particle size measuring device D for the image shown in Figure 12A. Comparing Figure 12B with Figure 12A, it can be seen that the particle size measuring device D in this embodiment can measure particle size with high accuracy.

As described above, the particle size measuring device D in the first embodiment and the particle size measuring method and particle size measuring program implemented therein obtain statistical features based on the relationship between the pixel values of the first and second pixels from the image of the measurement target and convert them into particle size (particle diameter), so that the particle size can be measured more accurately and therefore the particle size distribution (particle size distribution) can be obtained more accurately. Compared to a particle size measuring method that uses only frequency analysis with a power spectrum, the particle size measuring device D, particle size measuring method and particle size measuring program can measure particle size more robustly when there is a change in brightness of the entire image or when the illuminance changes gradually within the image.

The particle size measuring device D, particle size measuring method, and particle size measuring program obtain statistical features of an area and convert them into particle size, so that the particle size to be detected can be selected by adjusting the size (size, area) of the area. This allows the proportion of the individual fine particulate matter to be measured more accurately when a mixture of individual fine particulate matter and fine particulate matter attached to or stacked on large particulate matter is captured in the image of the measurement target. The particle size measuring device D, particle size measuring method, and particle size measuring program obtain statistical features of an area and convert them into particle size, so that the positions of small and large particulate matter can be identified at the same time as the particle size distribution of the entire image.

The particle size measuring device D, particle size measuring method, and particle size measuring program described above can obtain statistical features through simple information processing (simple arithmetic processing) by using a co-occurrence matrix.

The particle size measuring device D, particle size measuring method, and particle size measuring program provide illumination, so particle size can be measured under a constant lighting environment, reducing variation in measurement accuracy.

Next, another embodiment (second embodiment) will be described. In the second embodiment, the above-mentioned particle size measuring device is applied when adjusting the granulation conditions in a granulation system.

Figure 13 is a schematic diagram showing the configuration of a granulation system in the second embodiment. Figure 14 is a schematic diagram of a drum mixer in a granulation device of the granulation system. Figure 14A is a perspective view from the side, and Figure 14B is a vertical cross-sectional view. Figure 15 is a block diagram showing the electrical configuration of a granulation control device in the granulation system.

The granulation system S in the second embodiment is a system that granulates granular material from raw materials, dries and sinters the granulated granular material. In this embodiment, as an example, the granular material is a granulated product of iron ore obtained by adding quicklime as a binder to powdered ore as the raw material, and adding a predetermined amount of water to granulate the granulated product, and the granulated product becomes the sintered ore by drying and sintering. A predetermined auxiliary material is added to the raw material as necessary. For example, as shown in Figures 13 to 15, such a granulation system S includes a storage tank SR, a carry-in conveyor BC-1, a granulator DM, an unloading conveyor BC-2, an ore supply hopper HP, a sintering machine (sintering furnace) BK, conveyors 9 (9-1 to 9-3), and a granulation control device A.

The storage tank SR is a tank (container) for storing materials for producing sintered ore, such as raw materials and binders, and is provided in a number according to the type of material, for example. In the example shown in FIG. 13, a first storage tank SR-1 for storing a first type of fine ore, a second storage tank SR-2 for storing a second type of fine ore different from the first type, and a third storage tank SR-3 for storing quicklime as a binder are provided. Fine ore is the raw material for the sintered ore, and generally has different properties depending on the production area (brand), for example, porous fine ore and fine ore with a smooth surface. The porous fine ore requires a relatively large amount of water for granulation, while the smooth-surfaced fine ore can be granulated with a relatively small amount of water. In addition, the particles of the fine ore are attached to each other by the surface tension of the water, so the more water there is, the larger the particle size tends to be. In the production of granulated material for sintered ore production, the particle size of the granulated material Ob is related to the amount of water added during granulation, depending on the mixing ratio of the fine ores (the percentage of each type relative to the total (mass%)) and the amount of moisture contained in the fine ore before granulation. Granulation is promoted by the quicklime binder, so the particle size of the granulated material Ob is also related to the amount of quicklime added. Quicklime contains many fine particles, so it is easy to fill the gaps between the particles of the fine ore. Therefore, the more quicklime added, the less powder peels off from the granulated material and the larger the particle size becomes.

The input conveyor BC-1 is, for example, a belt conveyor that transports the material discharged from the storage tank SR to the granulator DM. In this embodiment, the material stored in the storage tank SR is dropped from the storage tank SR onto a sub-conveyor (not shown in FIG. 13, see FIG. 15) 9 (9-1 to 9-3) and discharged, and the material discharged from the storage tank SR is transported to the main input conveyor BC-1 by this sub-conveyor. Since the amount of material discharged from the storage tank SR per unit time is approximately constant, the amount of material transported to the granulator DM via the input conveyor BC-1 can be adjusted by adjusting the transport speed of the sub-conveyor 9. In the example shown in Figures 13 to 15, a sub-first conveyor (not shown in Figure 13, see Figure 15) 9-1 is provided in the first storage tank SR-1, and the first type of fine ore discharged from the first storage tank SR-1 is conveyed to the carry-in conveyor BC-1 by this sub-first conveyor 9-1, and the amount of the first type of fine ore conveyed to the granulator DM is adjusted by adjusting the conveying speed of the sub-first conveyor 9-1. A sub-second conveyor (not shown in Figure 13, see Figure 15) 9-2 is provided in the second storage tank SR-2, and the second type of fine ore discharged from the second storage tank SR-2 is conveyed to the carry-in conveyor BC-1 by this sub-second conveyor 9-2, and the amount of the second type of fine ore conveyed to the granulator DM is adjusted by adjusting the conveying speed of the sub-second conveyor 9-2. The mixing ratio of the powdered ores is adjusted by adjusting the amount of the first type of fine ore and the amount of the second type of fine ore, i.e., the conveying speed of the sub-first conveyor 9-1 and the conveying speed of the sub-second conveyor 9-2. A sub-third conveyor 9-3 (not shown in FIG. 13, see FIG. 15) is disposed in the third storage tank SR-3, and the quicklime discharged from the third storage tank SR-3 is conveyed to the conveyor BC-1 by this sub-third conveyor 9-3, and the amount of the quicklime (the amount of quicklime added) conveyed to the granulator DM is adjusted by adjusting the conveying speed of the sub-third conveyor 9-3.

The granulator DM is a device that granulates granular material from the material of the storage tank SR carried in via the carry-in conveyor BC-1 under predetermined granulation conditions, and is, for example, a drum mixer DM. In the example shown in FIG. 13, the granulator DM adds quicklime as a binder to the raw materials of the first and second fine ores, and adds a predetermined amount of water to granulate the granulated material. The drum mixer DM has a cylindrical drum body DB that is inclined downward from one end to the other end in the longitudinal direction, as shown in FIG. 14, for example, and the material of the storage tank SR (the first and second fine ores and quicklime materials in this example) carried in via the carry-in conveyor BC-1 is fed into the drum body DB from the one end of the drum body DB. Inside the drum body DB, a water spray nozzle SN that sprays water is arranged at a position that is a predetermined distance from the one end of the drum body DB and is the center of the inside of the drum body DB. A water supply pipe (water guide pipe) WP that supplies (guides) water to the water spray nozzle SN is connected to the water spray nozzle. An adjustment valve 8, such as an electromagnetic valve, is interposed in the water supply pipe WP to adjust the amount of water supplied to the water spray nozzle SN. By adjusting the opening of the adjustment valve 8, the flow rate through the water supply pipe WP is adjusted, and the amount of water supplied to the water spray nozzle SN is adjusted. This adjusts the amount of water added to the material in the drum body DB. On the inner wall of the drum body DB, four rod-shaped (columnar) first to fourth lifter bars LB-1 to LB-4 are arranged at equal intervals in the circumferential direction and parallel to each other along the longitudinal direction of the drum body DB. The drum body DB rotates in a predetermined direction by a rotation drive mechanism (not shown). When the drum body DB rotates, the materials in the drum body DB are successively hooked by the first to fourth lifter bars LB-1 to LB-4 and lifted up as the drum body DB rotates, and then fall by gravity. As a result, in the region (mixing region) between the one end of the drum body DB and where the water sprayed by the water spray nozzle SN falls, the materials in the drum body DB are mixed, in the region (hydration granulation region) where the water sprayed by the water spray nozzle SN falls, hydration granulation is performed, and in the region (non-hydration rolling region) between where the water sprayed by the water spray nozzle SN stops falling and the other end of the drum body DB, tumbling granulation is performed without adding water. The granulated material Ob granulated by the granulator DM is discharged from the other end of the drum body DB.

The transport conveyor CB-2 is, for example, a belt conveyor that transports the granulated material Ob discharged from the granulator DM to the ore supply hopper HP.

The ore supply hopper HP is a device that temporarily stores the granulated material Ob to be charged into the sintering machine (firing furnace) BK, and the granulated material Ob is charged into the sintering machine BK from the ore supply hopper HP.

The sintering machine (firing furnace) BK is a device that dries and fires the granulated material Ob that is charged from the ore supply hopper HP to produce sintered ore. In general, this sintering machine BK ignites the top of the layered stack of charged granulated material Ob and transfers the combustion by drawing in air from the bottom. In this way, the granulated material Ob charged into the sintering machine BK is dried and fired to become sintered ore.

As described above, the sintering machine BK dries and sinters the granulated material Ob, so gaps are necessary in the stack to allow air to flow through. Normally, granulated material Ob that does not exceed 2 mm in size deteriorates the air permeability and reduces the productivity of sintered ore. Therefore, in order to avoid the generation of granulated material Ob that deteriorates the air permeability in the sintering machine BK, in this embodiment, the granulation control device A provided in the granulation system S includes the above-mentioned particle size measuring device D.

More specifically, as shown in FIG. 15, the granulation control device A includes an image acquisition unit 1 equipped with a camera 1a and lighting devices 1b and 1c, a control processing unit 2a, a memory unit 3a, an input unit 4a, an output unit 5a, an IF unit 6a, a moisture meter 7, an adjustment valve 8, and the first to third conveyors 9-1 to 9-3 described above.

The image acquisition unit 1 equipped with the camera 1a and the lighting devices 1b, 1c is similar to the image acquisition unit 1 in the particle size measuring device D in the first embodiment, and therefore a description thereof will be omitted. Here, in the granulation system S, the camera 1a and the lighting devices 1b, 1c are arranged between the exit side of the granulator DM and the entry side of the ore feed hopper HP in order to continuously measure the particle size of the granulated material Ob, and in the example shown in FIG. 13, they are arranged in a position near the granulator DM so as to capture an image of the granulated material Ob being transported on the discharge conveyor BC-2 from directly above in order to measure the state of the granulated material Ob discharged from the granulator DM.

In order to keep the distance between the granulated material Ob and the camera 1a approximately constant, a so-called leveling plate may be further provided to level the top of the granulated material piled up on the discharge conveyor BC-2 and to keep the height of the granulated material piled up on the discharge conveyor BC-2 constant. Also, since there is a risk that steam generated from the granulated material Ob due to the heat of hydration of quicklime may obstruct the field of view of the camera 1a, a so-called air purge may be provided to blow off the steam.

The input section 4a is similar to the input section 4 in the particle size measuring device D in the first embodiment, except that commands and data related to granulation control are further input, so its description is omitted. The output section 5a is similar to the output section 5 in the particle size measuring device D in the first embodiment, except that commands and data related to granulation control are further output, so its description is omitted. The IF section 6a is similar to the IF section 6 in the particle size measuring device D in the first embodiment, except that data related to granulation control is further input/output between the IF section 6a and an external device, so its description is omitted.

The moisture meter 7 is connected to the control processing unit 2a and is a device that measures the moisture content of the granulated material Ob under the control of the control processing unit 2a, and the measurement result is output to the control processing unit 2a. The moisture meter 7 is, for example, an infrared moisture meter that irradiates the measurement object with near-infrared rays and measures the moisture content based on the amount of reflection. The correspondence between the amount of reflection and the moisture content is found and stored as a so-called calibration curve. This infrared moisture meter is a measurement meter that utilizes the fact that the absorption rate of a specific wavelength (e.g., 1.45 μm, 1.94 μm, etc.) in near-infrared rays differs depending on the moisture content in the substance. The moisture meter 7 is placed close to the camera 1a.

The adjusting valve 8 is connected to the control processing unit 2a, and is a device that adjusts the flow rate through the water supply pipe WP by adjusting its opening according to the control of the control processing unit 2a, as described above. This adjusts the amount of water supplied to the watering nozzle SN, and thus the amount of water added to the material in the drum body DB.

The first through third conveyors 9-1 through 9-3 are each connected to the control processing unit 2a, and are devices that adjust the amount of each material being fed into the granulator DM by adjusting their conveying speed as described above, according to the control of the control processing unit 2a.

The memory unit 3a is similar to the memory unit 3 in the particle size measuring device D in the first embodiment, except that it further stores programs and data related to granulation control. That is, the control processing program includes, in addition to the control program, the statistical feature processing program, and the particle size processing program, an adjustment program that adjusts the specified granulation conditions based on the particle size of the granular material (the granulated material in this example) determined by the particle size processing program. The various specified data include the image of the measurement target acquired by the image acquisition unit 1, the correspondence information, and other data required to execute each of these programs, such as the target value for granulation control.

The control processing unit 2a is a circuit that controls each of the units 1, 3a to 6a, 7, 8, 9-1 to 9-3 of the granulation control device A according to the function of each unit, measures the particle size of the granulated product Ob to be measured, and controls granulation. The control processing unit 2a is configured, for example, with a CPU and its peripheral circuits. By executing a control processing program, the control processing unit 2a is functionally equipped with a control unit 21a, a statistical feature amount processing unit 22, a particle size processing unit 23, and an adjustment unit 24. The statistical feature amount processing unit 22 and the particle size processing unit 23 are similar to the statistical feature amount processing unit 22 and the particle size processing unit 23 in the particle size measuring device D in the first embodiment, respectively, and therefore their description will be omitted.

The control unit 21a controls each of the units 1, 3a to 6a, 7, 8, 9-1 to 9-3 of the granulation control device A according to the function of each unit, and is responsible for the overall control of the granulation control device A.

The adjustment unit 24 adjusts the predetermined granulation conditions based on the particle size of the granulated material Ob determined by the particle size processing unit 23. As described above, the particle size of the granulated material Ob is affected by the mixing ratio of the powdered ore, the amount of quicklime added, and the predetermined amount of moisture, each of which can be a granulation condition for granulating the granulated material Ob to a target particle size. For this reason, in this embodiment, the adjustment unit 24 adjusts at least one of the mixing ratio, the amount of quicklime added, and the predetermined amount of moisture when the powdered ore contains multiple types.

As described above, granulated material Ob not exceeding 2 mm usually deteriorates the air permeability in the sintering machine BK and reduces the productivity of sintered ore, so the purpose of the granulation control device A is to control the amount of granulated material Ob not exceeding 2 mm (i.e., the amount of granulated material Ob with a particle size of 2 mm or less). The target value of the granulation control is set by the amount of granulated material Ob not exceeding 2 mm, and is, for example, a predetermined range (target range) defined by its upper and lower limits. Therefore, more specifically, the adjustment unit 24 adjusts at least one of the mixing ratio when the fine ore contains multiple types, the amount of quicklime added, and the predetermined amount of moisture so that the amount of granulated material Ob not exceeding 2 mm is within the target range based on the particle size of the granulated material Ob obtained by the particle size processing unit 23. Note that the lower limit may be set to 0, and the target range may be set only by the upper limit.

Here, particles with a particle size of 2 mm or less are defined as "powder", and the content of "powder" in the measurement target (the ratio of powder to the entire measurement target) is defined as the "fineness ratio". In more detail, based on the particle size of the granulated product Ob determined by the particle size processing unit 23, the adjustment unit 24 adjusts at least one of the mixing ratio when the powdered ore contains multiple types, the amount of quicklime added, and the predetermined amount of moisture so that the fineness ratio % of the granulated product Ob is within the target range (e.g., 10% to 30%, or 30% or less).

The control processing unit 2a, memory unit 3a, input unit 4a, output unit 5a, and IF unit 6a can be configured, for example, by a desktop or notebook computer. The computers that configure each of these units 2a to 6a are placed, for example, in an operation room in the granulation system S and may be incorporated into a console (or may serve as the console), or may be separate from the console.

In this embodiment, the input conveyor BC-1, the granulator DM, and the output conveyor BC-2 correspond to an example of a granulation section, and the granulation control device A including the particle size measuring device D, the input conveyor BC-1, the granulator DM, and the output conveyor BC-2 correspond to an example of a granulation device.

Next, the operation of this embodiment will be described. Figure 16 is a flowchart showing the operation of the granulation control device regarding the adjustment of granulation conditions.

When the granulation system S is operated and the power is turned on, the granulation control device A including the particle size measuring device D initializes the necessary parts and starts its operation. In the control processing unit 2a, a control unit 21a, a statistical feature processing unit 22, a particle size processing unit 23, and an adjustment unit 24 are functionally configured by executing the control processing program.

The granulation control device A repeatedly executes each process shown in FIG. 16 at a preset time interval (e.g., 0.5 hour interval, 1 hour interval, 2 hour interval, etc.) to adjust the granulation conditions.

In FIG. 16, the granulation control device A measures the powder ratio of the granulated material Ob (S11). More specifically, the granulation control device A operates in the same manner as the particle size measuring device D in the first embodiment, generating an image of the granulated material Ob with the camera 1a, dividing the image into a plurality of regions, obtaining statistical features for each region, obtaining particle diameters for each region, and obtaining a particle diameter distribution (particle size distribution) in the image of the measurement object. Then, the granulation control device A obtains the powder ratio from the obtained particle diameter distribution by the adjustment unit 24 of the control processing unit 2a. For example, the ratio of the sum of the frequency of each class of 2 mm or less to the sum of the frequency of each class in the particle diameter distribution (= ((sum of each frequency of each class of 2 mm or less) / (sum of each frequency of each class in the particle diameter distribution)) × 100) is obtained as the powder ratio [%]. Alternatively, for example, the powder ratio may be obtained in area %. The powder rate in area % is the percentage of the area of the powdered granulated material Ob relative to the total area of the granulated material Ob captured in the image (= (total area of the powdered granulated material Ob) / (total area of the granulated material Ob captured in the image) × 100). The area is expressed, for example, as the number of pixels. Alternatively, for example, the actual area captured in one pixel for each pixel position is obtained in advance, and the area is expressed as the actual area. Note that the particle size distribution at each sampling timing is obtained and each powder rate is obtained by repeating the process at a predetermined sampling interval (for example, 5 seconds or 10 seconds) for a predetermined period of time (for example, 1 minute or 2 minutes), and the average value of these powder rates may be used as the powder rate of the processing result of step S11 (final powder rate).

Next, the granulation control device A uses the adjustment unit 24 to determine whether the dust ratio determined in process S11 is within the target range (S12). If the result of this determination is that the dust ratio determined in process S11 is within the target range, that is, if the dust ratio determined in process S11 is equal to or greater than the lower limit of the target range and equal to or less than the upper limit of the target range (YES, OK), the granulation control device A ends this process and ends the process at this adjustment timing. On the other hand, if the result of the determination is that the dust ratio determined in process S11 exceeds the target range, that is, if the dust ratio determined in process S11 is below the lower limit of the target range or if the dust ratio determined in process S11 is above the upper limit of the target range (NO, NG), the granulation control device A then executes process S13.

In this process S13, the granulation control device A selects the target for adjusting the granulation conditions by the adjustment unit 24. In this embodiment, the adjustment unit 24 selects one of the moisture content, the amount of quicklime added, and the mixing ratio of the fine ore. The selection is made according to a preset rule. For example, from the viewpoint of cost, the moisture content, the amount of quicklime added, and the mixing ratio of the fine ore are selected in that order. In this case, the moisture content is selected first, and the granulation control device A then executes process S14-1. For example, when the particle size cannot be fully adjusted within the adjustable range of the moisture content (i.e., when the particle size cannot be fully adjusted even if the moisture content is set to 0, and when the particle size cannot be fully adjusted even if the moisture content is set to the maximum amount), or when further water cannot be added to the moisture content of the granulated material measured by the moisture meter 7, the amount of quicklime added is selected, and the granulation control device A then executes process S14-2. The maximum amount of moisture may be determined by the maximum flow rate of the water supply pipe WP, but may also be determined by taking into account the amount of heat generated by firing, since the sintering machine BK must compensate for the amount of heat generated by firing, which is equivalent to the increase in heat of evaporation due to the increase in the amount of water. For example, if the particle size cannot be adjusted within the adjustable range of the amount of quicklime added (i.e., if the particle size cannot be adjusted even if the amount of quicklime added is the minimum amount required as a binder, and if the particle size cannot be adjusted even if the amount of quicklime added is the maximum amount), or if the amount of quicklime added cannot be changed relative to the amount (remaining amount) of quicklime stored in the third storage tank SR-3, the mixing ratio of the fine ore is selected, and the granulation control device A then executes process S14-3.

In the process S14-1, the granulation control device A adjusts the amount of water sprayed by the water spray nozzle SN by controlling the opening of the adjustment valve 8 by the adjustment unit 24, ends this process, and ends the process at the current adjustment timing. For example, if the powder rate obtained in the process S11 is below the lower limit of the target range, the adjustment unit 24 controls the opening of the adjustment valve 8 so as to reduce the amount of water sprayed from the water spray nozzle SN by a predetermined amount (first predetermined amount) in order to increase the powder rate (to increase the granulated material Ob with a small particle size). Alternatively, for example, if the powder rate obtained in the process S11 is above the upper limit of the target range, the adjustment unit 24 controls the opening of the adjustment valve 8 so as to increase the amount of water sprayed from the water spray nozzle SN by a predetermined amount (second predetermined amount) in order to decrease the powder rate (to increase the granulated material Ob with a large particle size). The first predetermined amount and the second predetermined amount may be the same value or different values.

In the process S14-2, the granulation control device A adjusts the amount of quicklime added by controlling the conveying speed of the third conveyor 9-3 by the adjustment unit 24, ends this process, and ends the process at the current adjustment timing. For example, if the fineness rate obtained in the process S11 is below the lower limit of the target range, the adjustment unit 24 controls the conveying speed of the third conveyor 9-3 to reduce the amount of quicklime added by a predetermined amount (third predetermined amount) in order to increase the fineness rate (to increase the granulated material Ob with a small particle size). Alternatively, for example, if the fineness rate obtained in the process S11 is above the upper limit of the target range, the adjustment unit 24 controls the conveying speed of the third conveyor 9-3 to increase the amount of quicklime added by a predetermined amount (fourth predetermined amount) in order to decrease the fineness rate (to increase the granulated material Ob with a large particle size). The third predetermined amount and the fourth predetermined amount may be the same value or may be different values.

In the process S14-3, the granulation control device A adjusts the mixing ratio of the fine ore by controlling the conveying speeds of the first and second conveyors 9-1 and 9-2 using the adjustment unit 24, ends this process, and ends the process at the current adjustment timing. Since the ease with which the particle size increases (or decreases) varies depending on the type of fine ore, an algorithm is set in advance to adjust the mixing ratio of the fine ore depending on the type of fine ore. For example, if the fineness ratio determined in process S11 is below the lower limit of the target range, in order to increase the fineness ratio, the adjustment unit 24 controls the conveying speeds of the first and second conveyors 9-1 and 9-2 so as to adjust the mixing ratio of the fine ore by a predetermined amount (fifth predetermined amount) set in advance according to the algorithm. Alternatively, for example, if the fineness rate determined in step S11 exceeds the upper limit of the target range, in order to reduce the fineness rate, the adjustment unit 24 controls the conveying speeds of the first and second conveyors 9-1 and 9-2 so as to adjust the mixing ratio of the fine ore by a predetermined amount (sixth predetermined amount) set in advance according to the algorithm. The fifth predetermined amount and the sixth predetermined amount may be the same value or may be different values.

As described above, each of these processes is repeatedly executed at a predetermined time interval that has been set in advance. Therefore, if any of the processes S14-1 to S14-3 was executed at the previous adjustment timing, the process S12 at the current adjustment timing is also a process for confirming the effect. That is, if the result of the judgment in the process S12 at the current adjustment timing is that the powder ratio obtained in the process S11 is within the target range (YES, OK), it is confirmed that the previous adjustment was effective, and this process at the current adjustment timing is terminated. On the other hand, if the result of the judgment in the process S12 at the current adjustment timing is that the powder ratio obtained in the process S11 exceeds the target range (NO, NG), it is confirmed that the previous adjustment was ineffective, or that the effect of the previous adjustment was insufficient, and any of the processes S14-1 to S14-3 is executed at the current adjustment timing. That is, the adjustment of the granulation conditions is continued. In addition, even if the adjustment of the granulation conditions is stopped, if the result of the judgment in step S12 at any subsequent adjustment timing is that the powder ratio determined in step S11 exceeds the target range (NO, NG), the adjustment of the granulation conditions is resumed. Therefore, while the granulation system S is operating, the granulation control device A can continuously control the powder ratio so that it is within the target range.

In the above description, the adjustment unit 24 selects one of the processes S14-1 to S14-3 to adjust the granulation conditions, but if the powder ratio determined in process S11 exceeds the target range (NO, NG), the adjustment unit 24 may output an alarm from the output unit 5a to prompt the user (operator) to select one of the processes S14-1 to S14-3, accept the user's selection of one of the processes S14-1 to S14-3 at the input unit 4a, and execute one of the processes S14-1 to S14-3 according to the accepted selection. Furthermore, instead of being selected by the user, processes S14-1 to S14-3 may be automated within a system that controls granulation.

In addition, in the above description, the adjustment unit 24 selected one of processes S14-1 to S14-3, but the adjustment unit 24 may select multiple processes S14-1 to S14-3 and execute them.

In the above description, when the adjustment unit 24 executes any one of the processes S14-1 to S14-3, the effect of the process is confirmed at the next adjustment timing. However, after the execution of any one of the processes S14-1 to S14-3, a process for confirming the effect of the process may be further provided. In this case, if the result of the effect confirmation shows that the process has been effective, the process (the current adjustment of the granulation conditions) is terminated, and if the process has been ineffective or has been effective but insufficient, the process is returned to process S13. This effect confirmation is performed a predetermined number of times so that it is within the predetermined time interval for the repetition of processes S11 to S14 (S14-1 to S14-3).

As described above, according to the second embodiment, a granulation control device A equipped with a particle size measuring device D and a granulation method implemented therein can be provided. The granulation system S, granulation control device A and granulation method implemented therein in the second embodiment adjust predetermined granulation conditions, so that granular material can be granulated with a predetermined target particle size.

The above-mentioned granulation system S, granulation control device A, and granulation method implemented therein can granulate iron ore granules Ob with a specified particle size.

In the example shown in FIG. 2B, a pair of lighting devices 1b and 1c are used for one camera 1a, but the number of lighting devices is not limited to two and may be any number. For example, four first to fourth lighting devices (e.g., LED lights, etc.) may be used for one camera 1a. These first to fourth lighting units are arranged so as to surround the camera 1a from all sides and illuminate the granulated material (an example of the granular material to be measured) Ob on the transport conveyors B-1 and B-2 and the discharge conveyor BC-2. More specifically, when a square is virtually set on a virtual plane parallel to the conveying surface of the conveyor, the camera 1a is arranged so that its optical axis passes through the center of the square (the intersection of two diagonals), and the first to fourth lighting devices are arranged so that their optical axes intersect with the conveying surface, one at each of the four corners (quadrangles) of the square. By illuminating from all sides, shadows caused by unevenness on the granulated material Ob disappear, and images can be captured under the same conditions, resulting in stable measurement. A light-shielding member (e.g., a blackout curtain) that is provided to cover such an illumination device and blocks light from outside may be used. An observation window is provided in the light-shielding member as necessary, and the camera 1a captures an image of the granulated material Ob through the observation window. In the second embodiment, the moisture meter 7 also measures the moisture content of the granulated material Ob through the observation window. The light-shielding member prevents so-called stray light, making the lighting environment more stable.

In order to express the present invention, the present invention has been described above adequately and sufficiently through the embodiments with reference to the drawings. However, it should be recognized that a person skilled in the art can easily modify and/or improve the above-mentioned embodiments. Therefore, unless the modification or improvement implemented by a person skilled in the art is at a level that deviates from the scope of the claims described in the claims, the modification or improvement is interpreted as being included in the scope of the claims.

D Particle size measuring device A Granulation control device S Granulation system 1 Image acquisition unit 1a Camera 1b, 1c Illumination device 2, 2a Control processing unit 3, 3a Storage unit 21, 21a Control unit 22 Statistical feature amount processing unit 23 Particle size processing unit 24 Adjustment unit 31 Correspondence relationship information storage unit

Claims (9)

an image acquisition unit that acquires an image of the measurement target by capturing an image of the measurement target granular substance;
a statistical feature amount processing unit that calculates a statistical feature amount based on a relationship between pixel values of a first pixel and a second pixel that is within a predetermined range with respect to the first pixel, from the image of the measurement target acquired by the image acquisition unit;
a correspondence information storage unit that stores correspondence information representing a correspondence relationship between the statistical feature amount and a particle size;
a particle size processing unit that uses the correspondence relationship information stored in the correspondence relationship information storage unit to determine a particle size corresponding to the statistical feature amount determined by the statistical feature amount processing unit,
the statistical feature amount processing unit obtains a co-occurrence matrix in the image of the measurement target acquired by the image acquisition unit, and obtains a correlation value between rows and columns in the obtained co-occurrence matrix as the statistical feature amount .
Particle size measuring device. the statistical feature amount processing unit divides the image of the measurement target into a plurality of regions and obtains each statistical feature amount for each of the plurality of regions;
2. The particle size measuring device according to claim 1. the predetermined range is a range adjacent to the first pixel,
The particle size measuring device according to claim 1 or 2 . Further comprising an illumination unit that illuminates the granular substance to be measured.
4. The particle size measuring device according to claim 1 . an image acquisition step of acquiring an image of the measurement target by capturing an image of the measurement target granular substance;
a statistical feature processing step of obtaining a statistical feature based on a relationship between pixel values of a first pixel and a second pixel within a predetermined range with respect to the first pixel from the image of the measurement target obtained in the image obtaining step;
a particle size processing step of determining a particle size corresponding to the statistical feature obtained in the statistical feature processing step by using correspondence information indicating a correspondence relationship between the statistical feature and particle size;
The statistical feature processing step obtains a co-occurrence matrix in the image of the measurement target acquired in the image acquisition step, and obtains a correlation value between rows and columns in the obtained co-occurrence matrix as the statistical feature .
Particle size measurement method. On the computer,
an image acquisition step of acquiring an image of the measurement target by capturing an image of the measurement target granular substance;
a statistical feature processing step of obtaining a statistical feature based on a relationship between pixel values of a first pixel and a second pixel within a predetermined range with respect to the first pixel from the image of the measurement target obtained in the image obtaining step;
a particle size processing step of determining a particle size corresponding to the statistical feature amount determined in the statistical feature amount processing step by using correspondence information indicating a correspondence relationship between the statistical feature amount and a particle size ,
The statistical feature processing step obtains a co-occurrence matrix in the image of the measurement target acquired in the image acquisition step, and obtains a correlation value between rows and columns in the obtained co-occurrence matrix as the statistical feature .
Particle size measurement program. a granulation unit for granulating a granular material from a raw material under predetermined granulation conditions;
5. The particle size measuring device according to claim 1 , wherein the particle size of the granular material granulated in the granulating unit is determined as the measurement target;
and an adjustment unit that adjusts the predetermined granulation conditions based on the particle size of the granular material determined by the particle size measuring device.
Granulation equipment. The granular material is a granulated product of iron ore obtained by adding quicklime as a binder to powder ore as the raw material and adding a predetermined amount of water to granulate the mixture,
The adjusting unit adjusts at least one of a mixing ratio when the fine ore includes a plurality of types, an amount of the quicklime added, and a predetermined amount of the moisture.
The granulating apparatus according to claim 7 . A granulation step of granulating a granular material from a raw material under predetermined granulation conditions;
The particle size measuring method according to claim 5 , wherein the particle size of the granular material granulated in the granulation step is determined as the measurement object;
and adjusting the predetermined granulation conditions based on the particle size of the granular material determined by the particle size measurement method.
Granulation method.

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