Information processing method, information processing device, information processing system, computer-readable medium, and method of operating a blast furnace

Abstract

The information processing method comprises a step of measuring profile data of sediment material including distance data to sediment material in which a plurality of particles are deposited or image data of sediment material; a step of detecting each of the plurality of particles based on the profile data; a step of calculating an index based on the profile data; and a step of extracting particles located in the surface layer among the sediment material based on the detection results of each of the plurality of particles and the index calculated based on the profile data.

Description

Technology Field

[0001] The present disclosure relates to an information processing method, an information processing device, an information processing system, an information processing program, and a blast furnace operation method. Background Technology

[0002] A device capable of measuring the particle size of each particle of an industrial raw material with a particle shape, such as coke, with high measurement precision is known (see, for example, Patent Document 1). Prior art literature

[0003] Japanese Patent Publication No. 2014-92494 The problem to be solved

[0004] When measuring the properties of deposited raw materials by extracting them through image processing, the measurement error of the properties of the particles deposited at the bottom increases because the particles deposited at the bottom are obscured by the particles overlapping on top. It is required to improve the measurement precision of particle properties by separating the upper and lower particles to measure their properties.

[0005] Therefore, the present disclosure aims to provide an information processing method, an information processing device, an information processing system, an information processing program, and a blast furnace operation method based on the measured characteristics of particles, which can improve the measurement precision of the characteristics of particles. means of solving the problem

[0006] An information processing method according to one embodiment of the present disclosure comprises: a step of measuring profile data of a sedimentary material including distance data to a sedimentary material in which a plurality of particles are deposited or image data of the sedimentary material; a step of detecting each of the plurality of particles based on the profile data; a step of calculating an index based on the profile data; and a step of extracting particles located on the surface layer among the sedimentary material based on the detection results of each of the plurality of particles and the index calculated based on the profile data.

[0007] An information processing device according to one embodiment of the present disclosure comprises a control unit that executes the information processing method.

[0008] An information processing system according to one embodiment of the present disclosure comprises the information processing device and a measuring device that outputs profile data of the sediment to the information processing device.

[0009] An information processing program according to one embodiment of the present disclosure executes the information processing method on a processor.

[0010] A blast furnace operation method according to one embodiment of the present disclosure includes a step of measuring the characteristics of raw materials charged into the blast furnace as the characteristics of the surface particles by executing the information processing method, and a step of setting the operation conditions of the blast furnace based on the measurement result of the characteristics of the raw materials. Effects of the invention

[0011] According to the information processing method, information processing device, information processing system, information processing program, and blast furnace operation method of the present disclosure, the measurement precision of particle characteristics can be improved. In addition, the measurement results of particle characteristics can be reflected in the blast furnace operation method. Brief explanation of the drawing

[0012] FIG. 1 is a schematic diagram showing an example of the configuration of an information processing system according to the present disclosure. FIG. 2 is a block diagram showing an example of the configuration of an information processing system according to the present disclosure. FIG. 3 is a flowchart illustrating an example of the sequence of an information processing method according to the present disclosure. Figure 4 is a diagram showing an example of profile data of sedimentary material. Figure 5 is a diagram showing particles detected from the profile data of Figure 4 distinguished as particle regions. Figure 6 is a diagram showing an example of an envelope generated as a curve that touches only the upper convex portion of the target signal. Figure 7 is a diagram showing an example of an envelope calculated for the profile data of sedimentary material. Figure 8a is a diagram showing an example of an envelope calculation path along the width direction of a conveyor. Figure 8b is a diagram showing an example of an envelope calculation path along the conveying direction of a conveyor. Figure 9 is a diagram showing an example of an image in which a true value area is superimposed on the profile data of sedimentary material. Figure 10 is a diagram showing an example of the determination results of surface particles and lower particles. Figure 11 is a graph showing an example of the correlation between the particle size of the sieve analysis and the particle size of the measurement. Specific details for implementing the invention

[0013] (Form for carrying out the invention)

[0014] Hereinafter, embodiments of an information processing system (100) (see FIG. 1 et al.), an information processing device (4) (see FIG. 1 et al.), and an information processing method according to the present disclosure are described based on the drawings. Each drawing is schematic and may differ from reality. Furthermore, the following embodiments are intended to illustrate devices or methods for embodying the technical concept of the present disclosure and are not intended to specify the configuration as described below. That is, the technical concept of the present disclosure may be modified in various ways within the technical scope described in the claims.

[0015] In manufacturing processes utilizing raw materials such as minerals, the particle size, shape, or particle size distribution of the raw materials affects the operation of the process. Therefore, it is required to measure and identify the characteristics of the raw materials in advance. Particularly in the operation of blast furnaces, it is important to determine the particle size distribution of raw materials, such as ore or coke, which affects air circulation within the furnace.

[0016] To determine the particle size distribution of raw materials, the particle size distribution can be analyzed by sampling the raw materials and sieving them. However, since analysis using a sieve takes time, it is difficult to reflect the analysis results in real-time blast furnace operation. Therefore, a technology to measure the particle size distribution of raw materials in real-time is required. For example, the particle size distribution of raw materials can be measured in real-time by acquiring an image or shape of the upper surface of the raw materials using a camera or a laser rangefinder.

[0017] To measure the particle size distribution of raw materials, it is considered to process image data captured from particle-shaped raw materials on a conveyor. In this case, when particle-shaped raw materials are deposited, the outline of the lower layer of raw materials deposited below the surface layer is obscured by the surface layer. Consequently, the particle size of the lower layer of raw materials is prone to being calculated as smaller than the actual size. In other words, the error in particle size calculation is likely to increase.

[0018] In addition, the grain size of only the surface layer of rocks in the rock group can be measured based on 3D shape data of the rock group deposited on the conveyor acquired using a laser rangefinder (see Reference 1 below). In this case, the computational load may increase in order to calculate the height for each point of individual rocks. Therefore, it is difficult to measure the grain size in real time.

[0019] Document 1: Matthew J. Thurley, Automated Online Measurement of Particle Size Distribution using 3D Range Data, IFAC Proceedings Volumes, 2009, 42, 134-139

[0020] According to the information processing system (100), information processing device (4), and information processing method of the present disclosure, among a plurality of deposited materials, a surface layer material can be extracted with ease and high precision. In addition, the characteristics of the surface layer material can be measured with ease and high precision. For example, in the operation of a manufacturing process such as a blast furnace, a surface layer material among raw materials such as coke or ore that are deposited and transported on a conveyor can be measured with ease and high precision. In addition, the characteristics such as particle size or shape of the surface layer material among the deposited coke or ore can be measured with high precision.

[0021] (Example configuration of the information processing system (100))

[0022] As shown in FIGS. 1 and 2, an information processing system (100) according to one embodiment comprises an information processing device (4) and a measuring device (3). In the information processing system (100), the measuring device (3) acquires information regarding particles (2) that are deposited and transported on a conveyor (1). The information processing device (4) detects particles (2) located on the surface layer among the deposited particles (2) and measures their characteristics.

[0023] In the present embodiment, the conveyor (1) is a coke conveyor used in a blast furnace in the steel industry, but is not limited thereto. Additionally, the particles (2) are coke, which is one of the raw materials used in the steel industry, but are not limited thereto. The particles (2) may include, for example, ore, sintered ore, pellets, limestone, or rock.

[0024] <Information processing device (4)>

[0025] The information processing device (4) is equipped with a control unit (40), a communication unit (48), an output unit (46), and an input unit (47). The control unit (40) may be configured to include at least one processor, such as a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit), to control and manage various functions of the information processing device (4). The control unit (40) may be configured with one processor or with multiple processors. The processor constituting the control unit (40) may realize the functions of the information processing device (4) by reading and executing a program stored in a memory unit described later.

[0026] The control unit (40) may be subdivided into components that realize various functions of the information processing device (4). In this embodiment, the control unit (40) includes a measurement unit (41), a detection unit (42), a calculation unit (43), a judgment unit (44), and a measurement unit (45). The operation of each component of the control unit (40) will be described later.

[0027] The control unit (40) may be equipped with a memory unit. The memory unit stores various information or data. For example, the memory unit may store a program executed in the control unit (40), or data used for processing executed in the control unit (40), or the result of processing. Additionally, the memory unit may function as a work memory of the control unit (40). The memory unit may be configured to include, for example, semiconductor memory, but is not limited thereto. For example, the memory unit may be configured as an internal memory of a processor used as the control unit (40), or as a hard disk drive (HDD) accessible from the control unit (40). The memory unit may be configured as a non-transient readable medium. The memory unit may be configured integrally with the control unit (40) or as a separate entity from the control unit (40).

[0028] The communication unit (48) may be configured to include a communication interface for communicating with other devices, such as a measuring device (3), via wired or wireless means. The communication interface may be configured to enable communication with other devices via a network. The communication unit (48) may be configured to include an input / output port for inputting and outputting data between other devices. The communication unit (48) transmits and receives necessary data and signals to and from a process computer or a higher-level system. The communication unit (48) may communicate based on wired communication standards or based on wireless communication standards. For example, wireless communication standards may include communication standards for cellular phones such as 3G, 4G, and 5G. Additionally, for example, wireless communication standards may include IEEE 802.11 and Bluetooth (registered trademark). The communication unit (48) may support one or more of these communication standards. The communication unit (48) is not limited to these examples and may communicate with other devices or input / output data based on various standards.

[0029] The output unit (46) outputs information obtained from the control unit (40). The output unit (46) may notify the user of information by outputting visual information, such as characters, shapes, or images, either directly or through an external device. The output unit (46) may be equipped with a display device and may be connected to the display device via a wired or wireless connection. The display device may include various displays, such as a liquid crystal display. The output unit (46) may notify the user of information by outputting auditory information, such as voice, either directly or through an external device. The output unit (46) may be equipped with a voice output device, such as a speaker, and may be connected to the voice output device via a wired or wireless connection. The output unit (46) may be equipped with a vibration device. The output unit (46) may notify the user of information not only of visual information, auditory information, or tactile information, but also of information that the user can perceive through other senses, either directly or through an external device.

[0030] The input unit (47) may include an input device that receives input from a user. The input device may include, for example, a keyboard or physical keys, or a pointing device such as a touch panel, a touch sensor, or a mouse. The input device is not limited to these examples and may include various other devices.

[0031] <Measuring device (3)>

[0032] In this embodiment, the measuring device (3) is configured by a laser rangefinder. The laser rangefinder emits laser light in a line shape along the width direction of the conveyor (1) (depth direction of the paper in FIG. 1) and measures the distance to the particle (2) to be measured for each line. The particle (2) moves in the transport direction as it is deposited and transported on the conveyor (1). The laser rangefinder measures the distance to the particle (2) in a line shape at a constant measurement cycle and can generate three-dimensional shape data of the particle (2) by accumulating the measured values ​​of the distance in each line.

[0033] The above-described method is a method for acquiring the three-dimensional shape of a workpiece by a so-called optical cutting method. As a measuring device (3), a laser rangefinder and a data processing means used to perform the optical cutting method may be employed.

[0034] The measurement area of ​​the laser rangefinder may be set to an area equal to the width of the conveyor (1), or may be set to an area larger than the width of the conveyor (1). The laser rangefinder may be configured to measure the entire particle (2) being transported by the conveyor (1).

[0035] By shortening the period during which the laser rangefinder measures the distance to the particle (2) in a line shape, the measurement density of the three-dimensional shape data can be increased. In this embodiment, the measurement frequency is set to 4 kHz (the measurement period in this case is 0.25 milliseconds).

[0036] The measuring device (3) is not limited to a laser rangefinder and may be configured with a distance measuring camera using the Time Of Flight (TOF) method. The measuring device (3) generates three-dimensional shape data of particles (2) deposited on the conveyor (1), or distance data from the measuring device (3) to the particles (2), and outputs it to an information processing device (4).

[0037] The measuring device (3) may be configured to include an imaging device, such as a camera, for example. The measuring device (3) photographs a deposited material containing a plurality of particles (2) deposited on a conveyor (1) and outputs the captured image to an information processing device (4). The measuring device (3) generates image data of the particles (2) deposited on the conveyor (1) and outputs it to the information processing device (4). Additionally, the measuring device (3) may use the image data to generate distance data from the measuring device (3) to the particles (2) and output it to the information processing device (4). For example, the measuring device (3) may be configured as a stereo camera that generates distance data by correlating two images using a stereo method with two cameras. Additionally, the measuring device (3) may convert the image data into distance data based on the correlation between the brightness of the image of the particles (2) and the distance to the particles (2) (for example, the higher the brightness, the closer that point is to the measuring device (3)).

[0038] (Example of operation of the information processing system (100))

[0039] In an information processing system (100), the control unit (40) of the information processing device (4) acquires three-dimensional shape data, distance data, or image data of particles (2) deposited on the conveyor (1) from the measuring device (3) via the communication unit (48). The three-dimensional shape data, distance data, or image data are also collectively referred to as profile data. Based on the profile data acquired from the measuring device (3), the control unit (40) extracts particles (2) located on the surface layer from the particles (2) deposited on the conveyor (1). Additionally, the control unit (40) measures the characteristics of the particles (2) located on the surface layer. The particles (2) deposited on the conveyor (1) are also referred to as deposited material. Among the deposited material, the particles (2) located on the surface layer are also referred to as surface particles (2S) (see FIG. 4, etc.). Among the sedimentary materials, particles (2) located in the lower layer below the surface layer are also referred to as lower layer particles (2D) (see FIG. 4, etc.).

[0040] <Extraction of surface particles (2S)>

[0041] Hereinafter, an example of operation in which the control unit (40) determines and extracts surface particles (2S) based on profile data of sedimentary material is described based on the sequence of the flowchart illustrated in FIG. 3. The control unit (40) can extract surface particles (2S) by executing an information processing method including the sequence of the flowchart illustrated in FIG. 3. The information processing method may be realized as an information processing program executed on a processor constituting the control unit (40). The information processing program may be stored in a non-transient computer-readable medium.

[0042] The control unit (40) measures profile data of the sediment material (step S1). Specifically, the control unit (40) may generate profile data of the sediment material by processing measurement data of the measuring device (3) in the measuring unit (41), or may acquire profile data of the sediment material from the measuring device (3). In this embodiment, the control unit (40) acquires an image showing distance data of the sediment material exemplified in FIG. 4 as profile data. In FIG. 4, the closer a point is to the measuring device (3), the higher the brightness of that point appears as a point of high brightness (a point of color close to white). Surface particles (2S) appear as high brightness (a color close to white). Lower particles (2D) appear as lower brightness (a color close to black) than surface particles (2S).

[0043] The control unit (40) detects particles (2) included in the sediment material (step S2). The profile data of the particles (2) being transported as sediment material on the conveyor (1) appears as a single profile data in which individual particles (2) cannot be distinguished. The control unit (40) needs to distinguish and detect individual particles (2) in order to extract surface particles (2S) from the sediment material or to measure the characteristics of surface particles (2S).

[0044] Specifically, the control unit (40) performs signal processing on profile data obtained by measuring the shape of the surface irregularities of the sediment material that are generated by the deposition of particles (2), and separates individual particles (2). For example, when measuring the particle size as a characteristic of each particle (2), the control unit (40) can calculate the particle size distribution by generating a histogram by counting the number of particles for each particle size interval based on the particle size of each separated particle (2).

[0045] The control unit (40) may perform a separation process of particles (2) based on a processing method called, for example, the Watershed algorithm (see Reference 2), in order to separate and identify a plurality of particles (2) included in the profile data of the sediment material as different materials.

[0046] Document 2: Meyer, F. (1992). Color image segmentation. In Proceedings of the International Conference on Image Processing and its Applications, pages 303--306.

[0047] The control unit (40) may separate and identify each particle (2) by setting a segment corresponding to each particle (2) by performing segmentation processing on the profile data of the sediment material.

[0048] In this embodiment, the control unit (40) detects individual particles (2) from the profile data of the sediment material using the algorithm described in the aforementioned document 2. As illustrated in FIG. 5, the detected individual particles (2) appear as regions of different colors in the profile data. Specifically, adjacent surface particles (2S) and lower particles (2D) in the profile data are separated into different regions. The region where the particles (2) are separated is also referred to as the particle region. That is, as illustrated in FIG. 5, individual particle regions are well extracted from the profile data of the sediment material.

[0049] The control unit (40) calculates an envelope (7) (see FIG. 6 or FIG. 7) of the profile data of the sediment material (step S3). The envelope (7) can be generated as a curve that touches only the upper convex portion of the target signal (6), as exemplified in FIG. 6, which is used in the field of voice signal processing or electrical signal processing. Additionally, the envelope (7) can be generated as a curve that touches the entire set of curves. The control unit (40) calculates the envelope (7) as a curve that touches only the upper convex portion of the upper line (8) connecting the upper portions of the profile data of the sediment material in the cross-section of the sediment material exemplified in FIG. 7. In FIG. 7, the horizontal axis direction corresponds to the width direction of the conveyor (1). The vertical axis direction corresponds to the height direction of the sediment material on the conveyor (1).

[0050] The control unit (40) may calculate the envelope (7) over the entire profile data by calculating the envelope along a path that scans the two-dimensional profile data of the sediment material. The path for calculating the envelope (7) is also referred to as the envelope calculation path (11) (see FIG. 8a and FIG. 8b). Specifically, the control unit (40) may calculate the envelope (7) in each path by using a line following the width direction of the conveyor (1) as the envelope calculation path (11), as exemplified in FIG. 8a. Additionally, the control unit (40) may calculate the envelope (7) along at least two directions of path. Specifically, the control unit (40) may calculate the envelope (7) in each path by using a line following the transport direction of the conveyor (1) as the envelope calculation path (11), as exemplified in FIG. 8b. The control unit (40) may calculate the envelope surface of the two-dimensional profile data of the sedimentary material. The envelope surface may be generated as a surface tangent to the entire given group of curves. The control unit (40) may generate the envelope line (7) or the envelope surface by executing library software that realizes the function of generating the envelope line (7) or the envelope surface.

[0051] In this embodiment, the control unit (40) generates an envelope map of the transport direction that appears as a matrix having 800 × 1000 elements by calculating an envelope (7) of 1000 lines (1 line contains 800 pieces of data) in the transport direction. Additionally, the control unit (40) generates an envelope map of the width direction that appears as a matrix having 800 × 1000 elements by calculating an envelope (7) of 800 lines (1 line contains 1000 pieces of data) in the width direction. That is, the control unit (40) generates an envelope map of the transport direction and the width direction by calculating an envelope (7) in an envelope calculation path (11) that follows each of the transport direction and the width direction. The envelope map may be said to have 800 × 1000 grid points.

[0052] The control unit (40) may calculate the envelope (7) along other directions, not limited to the transport direction and width direction. The control unit (40) may appropriately set the spacing of the envelope calculation path (11) in each direction. The narrower the spacing of the envelope calculation path (11), the more robustly and accurately the envelope (7) can be calculated for the complex shape of the particle (2) and the sediment material. The control unit (40) may set the spacing of the envelope calculation path (11) based, for example, on the size of the particle (2). The wider the spacing of the envelope calculation path (11), the lower the computational load can be.

[0053] The control unit (40) generates a difference map by calculating the difference between the profile data of the sediment material and the envelope (7) calculated in step S3 (step S4). Specifically, the control unit (40) calculates the difference in the height direction between the envelope (7) calculated for the profile data of the sediment material in the cross-section of the sediment material exemplified in FIG. 7 and the top line (8) connecting the top of the profile data of the sediment material. The difference between the top of the surface particle (2S) of the sediment material and the envelope (7) is represented as D1. The difference between the top of the lower particle (2D) of the sediment material and the envelope (7) is represented as D2. The control unit (40) generates a difference map by calculating the difference in the height direction between the envelope (7) and the top of the profile data of the sediment material at each grid point on the envelope map. In this embodiment, the control unit (40) generates a difference map for the envelope map in each of the transport direction and the width direction.

[0054] The control unit (40) generates a difference binarized map by associating a true value (1 or True, etc.) with grid points in the difference map where the difference value is less than the difference threshold value, and a false value (0 or False, etc.) with grid points where the difference value is greater than or equal to the difference threshold value (step S5). The control unit (40) may also associate a true value with grid points where the difference value is 0. The control unit (40) may set the difference threshold value to, for example, 0.25. Additionally, the control unit (40) generates a difference binarized map for the difference maps in the transport direction and the width direction, respectively. The control unit (40) generates a sum difference binarized map by summing the two difference maps by calculating a logical OR at each grid point of the two difference maps. A logical OR corresponds to an operation in which the result is true when at least one of the two logical values ​​is true.

[0055] The control unit (40) calculates the number of points corresponding to true values ​​among each particle area (step S6). The control unit (40) may generate a map in which a difference binarization map or a sum difference binarization map is superimposed on a map in which each particle (2), such as a surface particle (2S) or a lower particle (2D), is divided into particle areas as exemplified in FIG. 9. The area containing the points corresponding to true values ​​is indicated as a true value area (14) colored black. The control unit (40) counts the points corresponding to true values ​​among the points included in each particle area and calculates the number of points corresponding to true values.

[0056] The control unit (40) determines whether the calculated score of the point corresponding to the true value in the particle area is greater than or equal to the score threshold value (step S7). The control unit (40) may set the score threshold value to, for example, 50 points.

[0057] The control unit (40) determines that the particle (2) in the particle area of ​​the judgment target is a lower layer particle (2D) when the calculated score is not greater than or equal to the score threshold value (Step S7: NO), that is, when the calculated score is less than the score threshold value (Step S8). The control unit (40) does not have to determine that the particle (2) in the particle area of ​​the judgment target is a surface layer particle (2S) or a lower layer particle (2D). The control unit (40) determines that the particle (2) in the particle area of ​​the judgment target is a surface layer particle (2S) when the calculated score is greater than or equal to the score threshold value (Step S7: YES) (Step S9). The control unit (40) may set the particle area determined to be a surface layer particle (2S) as a surface layer judgment area (12) and the particle area determined to be a lower layer particle (2D) as a lower layer judgment area (13), as exemplified in FIG. 10.

[0058] The control unit (40) determines whether the particle (2) is a surface particle (2S) in the order of step S8 or S9, and then terminates the execution of the order of the flowchart of FIG. 3. The control unit (40) may repeat the order of steps S6 to S9 for other particle regions to determine whether the other particle (2) is a surface particle (2S). The control unit (40) may display or output the determination result of the surface particle (2S) by the output unit (46), or output the determination result of the surface particle (2S) to another device by the communication unit (48).

[0059] The control unit (40) may execute the measurement sequence of profile data in step S1 as a function of the measurement unit (41). The control unit (40) may execute the detection sequence of particles (2) in step S2 as a function of the detection unit (42). The control unit (40) may execute the calculation sequence of the envelope (7) in step S3 and the generation sequence of the difference map in step S4 as a function of the calculation unit (43). The control unit (40) may execute the sequence from the generation sequence of the difference binarization map in step S5 to the judgment sequence in step S8 or S9 as a function of the judgment unit (44).

[0060] The control unit (40) calculates the number of points corresponding to true values ​​in the order of step S6, and determines and extracts surface particles (2S) based on the score calculated in the order of step S7. The control unit (40) may determine that a particle area is a surface determination area (12) if at least one point in the particle area is corresponding to a true value. The control unit (40) may calculate the ratio of the number of points corresponding to true values ​​to the total number of points included in the particle area, and determine that the particle area is a surface determination area (12) if the ratio is greater than the ratio threshold value.

[0061] The control unit (40) may determine surface particles (2S) by using an envelope (7) or an envelope surface as an indicator. In addition to the envelope (7) or an envelope surface, the control unit (40) may generate data in which high-frequency components in the spatial frequency of the sediment profile data are attenuated, for example, and use it as an indicator. The control unit (40) may generate data in which high-frequency components are attenuated by passing the sediment profile data through a spatial frequency low-pass filter. The control unit (40) may extract surface particles (2S) from the sediment based on the detection results of each particle (2) and the indicator calculated based on the sediment profile data.

[0062] When the control unit (40) calculates the envelope (7) as a surface, it may set parameters of the algorithm for calculating the envelope (7) to adjust the degree to which the envelope (7) enters the concave portion of the profile data of the sedimentary material. When the control unit (40) generates data in which the high-frequency components of the profile data of the sedimentary material are attenuated as a surface, it may set the attenuation rate of the high-frequency components. The higher the value of the attenuation rate of the high-frequency components, the more difficult it becomes for the generated data to enter the concave portion of the profile data. The control unit (40) may receive input of setting information by a user from the input unit (47) and set the calculation parameters of the envelope (7) based on the input setting information.

[0063] As described above, according to the information processing device (4) and information processing method of the present embodiment, surface particles (2S) are extracted from sedimentary material based on a surface generated from profile data of sedimentary material. Specifically, the convex portion of the profile data of sedimentary material comes into contact with or approaches within a predetermined distance of a surface such as an envelope (7) or an envelope surface. The convex portion of the profile data corresponds to the upper part of the surface particles (2S). Accordingly, surface particles (2S) are extracted based on the positional relationship between the surface such as an envelope (7) or an envelope surface and the convex portion of the profile data. The information processing device (4) is also referred to as a surface material detection device that detects surface particles (2S).

[0064] The computational load for determining surface particles (2S) based on the surface can be reduced compared to the computational load for determining surface particles (2S) by analyzing the irregularities of the sediment material. Therefore, according to the information processing device (4) and information processing method according to the present embodiment, extraction of surface particles (2S) can be realized with a low computational load. In addition, as described below, measurement precision can be improved by measuring the characteristics of the extracted surface particles (2S). The simple extraction of surface particles (2S) contributes to the improvement of measurement precision of the characteristics of the surface particles (2S).

[0065] <Measurement of the characteristics of surface particles (2S)>

[0066] The control unit (40) measures the characteristics of the particle (2) determined to be a surface particle (2S). The control unit (40) may implement the function of measuring the characteristics of the particle (2) as a measuring unit (45). The control unit (40) may, for example, measure the particle size of the particle (2) as the characteristics of the particle (2).

[0067] The control unit (40) may measure the particle size of the surface particle (2S) by, for example, a circular approximation fitting method. The circular approximation fitting method is a method of approximating the area determined to be the surface particle (2S) from a true circle having the same area as the area determined to be the surface particle (2S), and calculating the diameter of the approximation circle as the particle size of the surface particle (2S). The control unit (40) may not be limited to the circular approximation fitting method and may measure the particle size of the surface particle (2S) by various other methods. The control unit (40) may display or output the measurement result of the surface particle (2S) by the output unit (46), or output the measurement result of the surface particle (2S) to another device by the communication unit (48).

[0068] Hereinafter, the precision of calculating the particle size of the particle (2) in the present embodiment is explained with reference to the graph in FIG. 11, which shows the correlation between the result of calculating the particle size of the particle (2) in the present embodiment and the particle size measured by sieve analysis. The particle size of the particle (2) in the present embodiment is a value measured from the profile data of a sedimentary material in which a plurality of particles (2) of a certain group are deposited. In addition, the particle size measured by sieve analysis is a value calculated by integrating and measuring the respective particle sizes of a plurality of particles (2) of the same group as the sedimentary material in which the particle size of the particle (2) in the present embodiment was measured, and calculating the average value of the particle sizes of each particle as the particle size of the group of particles (2). Specifically, a sedimentary material in which particles (2) are deposited is prepared, and the particle size of each particle (2) is measured from the profile data. In addition, after measuring the particle size from the profile data, the particle size of the particle (2) contained in the sedimentary material is measured by sieve analysis. The average value of the particle size measured from the profile data of the sediment is the average value of the particle size of only the particles (2) extracted as surface particles (2S). In addition, the average value of the particle size measured by sieve analysis is the average value of the particle size of all particles (2) including both surface particles (2S) and sub-layer particles (2D) contained in the sediment. In the graph of FIG. 11, the correlation between the average value of the particle size of only the particles (2) extracted as surface particles (2S) and the average value of the particle size of all particles (2) from sieve analysis is shown as a circular plot. The correlation coefficient (R^2) regarding the particle size of only the surface particles was calculated to be 0.62. In addition, in the graph of FIG. 11, the correlation between the average value of the particle size of all particles (2) including both surface particles (2S) and sub-layer particles (2D) and the average value of the particle size of all particles (2) from sieve analysis is shown as a rectangular plot. The correlation coefficient (R^2) for the combined particle size of the surface and lower layers was calculated to be 0.17.

[0069] Here, the particle size from the sieve analysis is considered to be close to the actual particle size. Furthermore, the higher the correlation coefficient between the measured particle size and the particle size from the sieve analysis, the closer the measured particle size is to the actual particle size. Therefore, the higher the correlation coefficient with the particle size from the sieve analysis, the higher the precision of the particle size measurement. As mentioned above, considering that the correlation coefficient regarding the particle size of the surface layer alone is higher than the correlation coefficient regarding the particle size of the surface layer and the lower layer combined, the precision of the measurement result of the particle size of the surface layer particle (2S) alone can be said to be higher than the precision of the measurement result of the particle size of the surface layer particle (2S) and the lower layer particle (2D) combined.

[0070] As described above, according to the information processing device (4) and information processing method of the present embodiment, the characteristics of the surface particles (2S) can be measured by excluding the lower particles (2D) from the sedimentary material and extracting only the surface particles (2S) that are not hidden by other particles (2). By doing so, the characteristics of the surface particles (2S) with no missing parts can be measured with high precision. In the present embodiment, the particle size of the particle (2) was measured as the characteristics of the particle (2). Various other items may be measured as the characteristics of the particle (2). For example, as the characteristics of the particle (2), the shape of the outline of the particle (2) may be measured based on the shape of the particle region. In addition, as the characteristics of the particle (2), the surface shape including pores or sintering holes on the surface of the particle (2) may be measured based on the fine irregularities of the profile data of the sedimentary material or the fine irregularities of the boundary of the particle region. In addition, the material of the particle (2) may be measured as a characteristic of the particle (2). The information processing device (4) is also referred to as a characteristic measuring device that measures the characteristic of the particle (2).

[0071] (Blast furnace operation method)

[0072] The properties of the coke used as a raw material for the blast furnace may be measured by the information processing device (4) and information processing method described above. That is, the particles (2) may be coke. The coke functions as a reducing agent and also functions as a spacer that secures a passage for high-temperature gas to rise within the blast furnace. Therefore, the particle size of the coke and the permeability within the blast furnace are closely related. If the particle size of the coke becomes excessively small, the permeability within the blast furnace decreases as the voids become smaller. A decrease in permeability can worsen the furnace conditions. By measuring the particle size of the coke in real time before charging the coke into the blast furnace, operating conditions can be set such that the furnace conditions do not worsen depending on the particle size of the charged coke.

[0073] Therefore, the operating conditions of the blast furnace may be set based on the characteristics of the particle (2) measured by the control unit (40) of the information processing device (4). The information processing device (4) may output the measurement results of the characteristics of the particle (2) to a device for setting the operating conditions of the blast furnace. The information processing device (4) may set the operating conditions of the blast furnace.

[0074] According to the information processing device (4) and information processing method according to the present embodiment, the particle size of the coke before it is charged into the blast furnace can be measured in real time. By measuring the particle size of the coke in real time, it becomes possible to intervene in the blast furnace operation method according to the coke particle size.

[0075] For example, if the particle size of the coke decreases, the porosity of the upper layer of the blast furnace may decrease. As the porosity decreases, it is expected that the air permeability within the blast furnace will deteriorate in the future. If it is expected that the air permeability within the blast furnace will deteriorate, operational intervention may be implemented to reduce the amount of hot air blown.

[0076] In addition, as another example, it is considered that the relationship between the size distribution of the grain size at the center and inner wall of the blast furnace varies in the vertical direction of the furnace. In this case, it is expected that the reaction within the blast furnace will not be promoted. If it is expected that the reaction within the blast furnace will not be promoted, operational intervention may be implemented to increase the ratio of coke to the ore charged into the blast furnace (coke ratio) in order to promote the reaction.

[0077] Although the embodiments of the present disclosure have been described based on the drawings and embodiments, those skilled in the art should note that various modifications or alterations can be made based on the present disclosure. Therefore, it should be noted that such modifications or alterations are included within the scope of the present disclosure. For example, functions included in each component or each step, etc., can be rearranged without logical contradiction, and multiple components or steps, etc., can be combined into one or divided. Embodiments according to the present disclosure can also be realized as a program executed by a processor equipped with a device or as a storage medium recording a program. It should be understood that these are also included within the scope of the present disclosure. Explanation of the symbols

[0078] 100 : Information processing system 1 : Conveyor 2 : Particles (2S: Surface particles, 2D: Bottom particles) 3: Measuring device 4 : Information processing device (40: control unit, 41: measurement unit, 42: detection unit, 43: calculation unit, 44: judgment unit, 45: measurement unit, 46: output unit, 47: input unit, 48: communication unit) 6 : Target signal 7: Envelope 8 : Top line 11: Envelope Calculation Path 12: Surface judgment area 13: Lower judgment area 14: True value range

Claims

Claim 1 A method for processing information, comprising: a step of measuring profile data of a sedimentary material including distance data to a sedimentary material in which a plurality of particles are deposited or image data of said sedimentary material; a step of detecting each of said particles based on said profile data; a step of calculating an index based on said profile data; and a step of extracting surface particles from said sedimentary material based on the detection result of each of said particles and said index, wherein the step of calculating the index includes calculating an envelope or an envelope surface of said profile data, and the step of extracting the surface particles extracts said surface particles based on a difference between said index and said profile data, and said difference includes a difference in the height direction. Claim 2 An information processing method comprising: a step of measuring profile data of a sedimentary material including distance data to a sedimentary material in which a plurality of particles are deposited or image data of the sedimentary material; a step of detecting each of the plurality of particles based on the profile data; a step of calculating an index based on the profile data; and a step of extracting surface particles from the sedimentary material based on the detection results of each of the plurality of particles and the index, wherein the step of calculating the index includes passing the profile data through a spatial frequency low-pass filter to produce data in which high-frequency components are attenuated, and the step of extracting the surface particles extracts the surface particles based on the difference between the index and the profile data, wherein the difference includes a difference in the height direction. Claim 3 An information processing method according to claim 1, further comprising a step of measuring the properties of surface particles extracted as surface particles from the sediment material. Claim 4 An information processing method according to paragraph 2, further comprising a step of measuring the characteristics of surface particles extracted as surface particles from the sediment material. Claim 5 In paragraph 3, an information processing method wherein, in the step of measuring the characteristics of the surface particles, the particle diameter or shape of the surface particles is measured as the characteristics of the surface particles. Claim 6 In paragraph 4, an information processing method wherein, in the step of measuring the characteristics of the surface particles, the particle diameter or shape of the surface particles is measured as the characteristics of the surface particles. Claim 7 An information processing device having a control unit that executes an information processing method described in any one of paragraphs 1 to 6. Claim 8 An information processing system comprising an information processing device described in claim 7 and a measuring device that outputs profile data of the sediment material to the information processing device. Claim 9 A computer-readable medium that stores an information processing program for executing an information processing method described in any one of paragraphs 1 through 6 on a processor. Claim 10 A method for operating a blast furnace, comprising the steps of: measuring the characteristics of raw materials charged into the blast furnace as the characteristics of the surface particles by executing an information processing method described in any one of paragraphs 3 to 6; and setting the operating conditions of the blast furnace based on the measurement result of the characteristics of the raw materials.

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