GUTTER MANAGEMENT SYSTEM AND GUTTER MANAGEMENT METHOD

Abstract

 A runner management system according to the present invention includes: a measurement device disposed above a runner toward the runner and configured to measure an inner surface shape of the runner; and a determination device configured to determine a wear state of the runner by using at least measurement data of the inner surface shape and a predetermined determination model.

Description

Field

[0001] The present invention relates to a runner management system and a runner management method.

Background

[0002] Various types of runners (including tapping runners, slag runners, tilting runners, molten iron runners) are used at the time of conveying molten iron discharged from a tap hole of a blast furnace and accompanying slag, and due to high-temperature molten pig iron or slag, these runners wear because of abrasion of refractory applied to an inner surface of these runners or due to a chemical change. In addition, the refractory applied to the inner surface of the runner wears due to repeated temperature rise/fall in situations such as switching of the tap holes. Since the wear of the refractory changes depending on the situation in this manner, it is necessary to measure the shape of the inner surface in order to determine the necessity of repair. However, the measurement, made by manual work, would take time, and involves other problems such as safety problems as well as a problem of measurement timing judgment. On the other hand, there is also a known device that enables measurement without manual work. For example, Patent Literature 1 discloses a measuring device, being a device provided to measure an inner surface shape of a blast furnace tapping runner, including at least a pair of optical wave distance measurement devices, a rotary drive device, and a control computation device. The at least one pair of optical wave distance measurement devices is provided above the blast furnace tapping runner so as to face each other in a width direction of the blast furnace tapping runner. The rotary drive device rotates the optical wave distance measurement device in two intersecting axial directions. The control computation device controls the orientation of the optical wave distance measurement device, and performs computation processing on the measurement data to obtain the inner surface shape of the blast furnace tapping runner.

Citation List

Patent Literature

[0003] Patent Literature 1: JP H09-241714 A

Summary

Technical Problem

[0004] The measuring device disclosed in Patent Literature 1 is useful in enabling measurement without manual work. However, the measurement position is restricted, and thus, when the operation differs from the past operation situation, and when a deviation occurs in the wear position, there is a possibility of occurrence of inappropriate repair judgment. When judging the necessity of repair in consideration of such a situation in the measurement data, there is also a problem of complicated management.

[0005] The present invention has been made in view of the above problems, and an object of the present invention is to provide a runner management system and a runner management method capable of simplifying management of various runners (including tapping runners, slag runners, tilting runners, molten iron runners) used in conveying molten iron discharged from a tap hole of a blast furnace and accompanying slag.

Solution to Problem

[0006] To solve the above-described problem and achieve the object,

(1) a runner management system according to the present invention includes: a measurement device disposed above a runner toward the runner and configured to measure an inner surface shape of the runner; and a determination device configured to determine a wear state of the runner by using at least measurement data of the inner surface shape and a predetermined determination model.

(2) The above-described runner management system according to (1) further includes a computation device configured to perform machine learning using a set of the measurement data dedicated for learning and the wear level of the runner as training data, using the measurement data as input, and using the wear level as output, so as to obtain a determination model designed to determine the wear level, as the predetermined determination model.

(3) The above-described runner management system according to (1) further includes a computation device configured to perform machine learning using a set of data dedicated for learning and indicating a use history of the runner as well as measurement data of the inner surface shape dedicated for learning, and a wear rate level of the runner as training data, using the data indicating the use history of the runner as well as measurement data of the inner surface shape as input, and using the wear rate level as output, so as to obtain a determination model designed to determine the wear rate level, as the predetermined determination model.

(4) The above-described runner management system according to any one of (1) to (3) further includes a display device configured to present continuation of use or end of use of the runner based on a determination result obtained by the determination device.

(5) In the above-described runner management system according to any one of (1) to (3), the measurement device is a 3D scanner.

(6) A runner management method according to the present invention includes: a step of measuring an inner surface shape of a runner by using a measurement device disposed above the runner toward the runner; and a step of determining a wear state of the runner by a determination device by using at least measurement data of the inner surface shape and a predetermined determination model.

(7) The above-described runner management method according to (6) further includes a step of performing, by a computation device, machine learning using a set of the measurement data dedicated for learning and the wear level of the runner as training data, using the measurement data as input, and using the wear level as output, so as to obtain a determination model designed to determine the wear level, as the predetermined determination model.

(8) The above-described runner management method according to (6) further includes a step of performing, by a computation device, machine learning using a set of data dedicated for learning and indicating a use history of the runner as well as measurement data dedicated for learning, and a wear rate level of the runner as training data, using the data indicating the use history of the runner as well as the measurement data as input, and using the wear rate level as output, so as to obtain a determination model designed to determine the wear rate level, as the predetermined determination model.

(9) The above-described runner management method according to any one of (6) to (8) further includes a step of presenting, on a display device, continuation of use or end of use of the runner based on a determination result obtained by the determination device.

(10) In the above-described runner management method according to any one of (6) to (8), the measurement device is implemented by using a 3D scanner.

Advantageous Effects of Invention

[0007] A runner management system and a runner management method according to the present invention have an effect of simplifying management of runners.

Brief Description of Drawings

[0008] 

FIG. 1 is a diagram schematically illustrating members such as a blast furnace and tapping runner according to an embodiment.

FIG. 2 is a cross-sectional view illustrating a structure of a tapping runner, which is newly provided or just repaired, according to the embodiment.

FIG. 3 is a cross-sectional view illustrating a wear state of the tapping runner according to the embodiment.

FIG. 4 is a diagram illustrating a schematic configuration of a runner management system according to the embodiment.

FIG. 5 is a flowchart illustrating a flow of runner repair guidance presentation processing performed by the runner management system.

FIG. 6 is a flowchart illustrating a flow of learning processing of a determination model designed to determine a wear level.

FIG. 7 is a diagram illustrating an example in which measurement data of a tapping runner is displayed on a display device of a management server.

FIG. 8 is a flowchart illustrating a flow of learning processing of a determination model designed to determine a runner wear rate level.

FIG. 9 is a flowchart illustrating a flow of a determination processing of continuation of use or end of use of a runner performed by the runner management system. Description of Embodiments

[0009] Hereinafter, an embodiment of a blast furnace runner management method according to the present invention will be described with an example of a tapping runner. The present invention is not limited to the present embodiment.

[0010] FIG. 1 is a diagram schematically illustrating members such as a blast furnace 1 and tapping runner 3 according to the embodiment. In FIG. 1, arrow A indicates a longitudinal direction of the tapping runner 3, arrow B indicates a width direction of the tapping runner 3, and arrow C indicates a height direction of the blast furnace 1. As illustrated in FIG. 1, the tapping runner 3 is disposed adjacent to a tap hole 2 provided in the blast furnace 1. Molten iron and slag discharged from the tap hole 2 fall and flow into the tapping runner 3 with parabolic trajectory.

[0011] FIG. 2 is a cross-sectional view illustrating a structure of the tapping runner 3, which is newly provided or just repaired, according to the embodiment. The tapping runner 3 has a structure in which an inner lining material 35 (wear lining materials of unshaped refractory materials to be an inner lining layer) is applied, by pouring or spraying, onto the inner surface side of a refractory, referred to as a back material 31 preinstalled in the tapping runner 3. In FIG. 2, reference numeral 32 denotes a refractory brick, reference numeral 33 denotes a precast block, reference numeral 34 denotes a steel jacket, and reference numeral 350 denotes an inner wall surface.

[0012] The shape of the inner wall surface 350 of the tapping runner 3 changes from a shape of the runner, which is newly provided or just repaired illustrated in FIG. 2, to a shape in which the inner wall surface 350 of the tapping runner 3 wears to have a recess as illustrated in FIG. 3 due to erosion by molten iron and slag fed out to the tapping runner 3. The molten iron and the slag are separated by a density difference while flowing through the tapping runner 3, and the upper side of the inner wall surface 350 of the tapping runner 3 wears mainly by the slag, while the lower side wears mainly by the molten iron. Therefore, in the present embodiment, the wear state of the inner wall surface 350 of the tapping runner 3 is detected, and the tapping runner 3 is repaired as necessary. In the following description, the wear or a wear state of the inner wall surface 350 of the tapping runner 3 may be simply described as the wear or the wear state of the tapping runner 3.

[0013] As illustrated in FIG. 1, the present embodiment performs detection of the wear state of the tapping runner 3 by using a 3D scanner 4, being a measurement device disposed above the tapping runner 3 toward the tapping runner 3 to measure the conditions such as the inner surface shape and dimensions of the tapping runner 3. FIG. 1 illustrates an example in which the 3D scanner 4, which is a measurement device of measuring conditions such as the inner surface shape and the dimensions of the tapping runner 3, is disposed in the longitudinal direction of the tapping runner 3. The present invention, however, is not limited thereto, and the 3D scanner 4 may be disposed in the width direction of the tapping runner 3. That is, a distance to the inner wall surface 350 of the tapping runner 3 is measured at a plurality of points, and the wear of the inner wall surface 350 of the tapping runner 3 is measured based on the measurement result. The 3D scanner 4 is a three-dimensional shape measurement device that measures a distance to each point, and can be implemented by using a laser, an electromagnetic wave radar, an ultrasonic wave, or the like. Among these devices, it is preferable to use a laser device capable of setting a wide measurement region and having high point-to-point resolution and high distance resolution. Hereinafter, a laser device will be described as an example.

[0014] The 3D scanner 4 is fixed to a tripod 6 installed on the floor of a scaffold 5 bridged above the tapping runner 3 so as to be able to image the tapping runner 3 from the downstream side to the upstream side in the longitudinal direction. The 3D scanner 4 can perform a scan using a laser emitted toward the tapping runner 3 to measure the distance, making it possible to measure the shape of the tapping runner 3 in a certain range of region. The 3D scanner 4 can perform the laser scan in a predetermined range in a fixed state by expanding the laser application range using a swing mechanism (mirror rotation) or the like.

[0015] With the measurement of the tapping runner 3 by the 3D scanner 4, a determination is made by comparing the pre-wear state and the post-wear state at a same location in the longitudinal direction of the tapping runner 3. Therefore, for example, as illustrated in FIG. 1, a plurality of checkerboards 9A, 9B, and 9C serving as references of measurement positions is installed in a fixture 8 fixed to the blast furnace 1. The plurality of checkerboards 9A, 9B, and 9C is a calibration component for enhancing positioning accuracy by reflecting laser signals from the 3D scanner 4 with high reflectance. By using the plurality of checkerboards 9A, 9B, and 9C as references of measurement positions, measurement data can be compared with high accuracy, enabling shape measurement with high precision. Incidentally, the plurality of checkerboards 9A, 9B, and 9C is installed with an interval of 1 [m] or more in the width direction of the tapping runner 3 indicated by arrow B in FIG. 1 and an interval of 1 [m] or more in the height direction of the blast furnace 1 indicated by arrow C in FIG. 1. In addition, the plurality of checkerboards 9A, 9B, and 9C is installed so as not to overlap each other in the height direction.

[0016] In addition, as illustrated in FIG. 1, at the edge of the tapping runner 3, there is a plurality of scales 7 indicating a distance from the tap hole 2 in the longitudinal direction of the tapping runner 3. The plurality of scales 7 can be used, for example, as a guide when an operator specifies a distance (position) from the tap hole 2 of the blast furnace 1 when visually confirming the wear position of the tapping runner 3. By adopting such a method, it is sufficient to use even one 3D scanner 4 for accurate measurement, but it is also allowable to install the 3D scanner 4 in plurality.

[0017] FIG. 4 is a diagram illustrating a schematic configuration of a runner management system 10 according to the embodiment. The runner management system 10 according to the embodiment mainly includes a 3D scanner 4, a mobile information terminal 20, and a management server 30.

[0018] The mobile information terminal 20 includes devices such as a control device 201, a storage device 202, a communication device 203, an input device 204, a display device 205, and an imaging device 206.

[0019] The control device 201 includes: a processor including a central processing unit (CPU); and memory (main storage unit) including random access memory (RAM) and read only memory (ROM). The control device 201 loads a program stored in the storage device 202 into a work area of the memory and executes a program, and controls each component device through the execution of the program, thereby implementing a function corresponding to a predetermined purpose.

[0020] The storage device 202 includes, for example, a recording medium such as a hard disk drive (HDD). The storage device 202 can store information such as an operating system (OS), various programs, various tables, and various databases.

[0021] The communication device 203 includes, for example, a wireless communication circuit for wireless communication such as Wi-Fi (registered trademark). The communication device 203 communicates with the 3D scanner 4 and the management server 30 by wireless communication.

[0022] The input device 204 and the display device 205 include, for example, a single touch panel display functioning as an input/output means. In a case where the touch panel display functions as the input device 204, for example, an operator operates the touch panel display to input predetermined information to the control device 201. The input device 204 can be used, for example, when an operator inputs characters indicating a wear state of the tapping runner 3. Furthermore, when functioning as the display device 205, for example, the touch panel display displays information such as characters, figures, and images on a screen of the touch panel display under the control of the control device 201, so as to present predetermined information to the outside.

[0023] The imaging device 206 includes, for example, an imaging element such as a Charge Coupled Device (CCD) image sensor and a CMOS image sensor. The imaging device 206 outputs data such as a captured image to the storage device 202. The imaging device 206 can be used, for example, when an operator images the wear state of the tapping runner 3 and stores the wear state of the tapping runner 3 as an image in the storage device 202 or the like.

[0024] The management server 30 includes devices such as a control device 301, a storage device 302, a communication device 303, an input device 304, and a display device 305.

[0025] The control device 301 includes, for example, a processor including a CPU and the like, and memory including RAM and ROM. The control device 301 loads a program stored in the storage device 302 into a work area of the memory and executes a program, and controls each component device through the execution of the program, thereby implementing a function corresponding to a predetermined purpose.

[0026] The storage device 302 includes, for example, a recording medium such as a hard disk drive (HDD). The storage device 302 can store information such as an operating system (OS), various programs, various tables, and various databases.

[0027] The communication device 303 includes, for example, a wireless communication circuit for wireless communication such as Wi-Fi (registered trademark). The communication device 303 communicates with the mobile information terminal 20 by wireless communication.

[0028] The input device 304 includes, for example, a keyboard and a mouse as input means. The input device 304 functions such that, when an operator operates the keyboard and the mouse, for example, predetermined information is input to the control device 301.

[0029] The display device 305 includes, for example, a display as an output means. For example, under the control of the control device 301, the display device 305 displays items such as characters, figures, and images on a screen of the display to present predetermined information to the outside.

[0030] The runner management system 10 according to the embodiment executes repair guidance presentation processing on the tapping runner 3 described below to accurately determine a wear state of the tapping runner 3 and manage necessity of repair of the tapping runner 3.

[0031] FIG. 5 is a flowchart illustrating a flow of repair guidance presentation processing on the tapping runner 3 performed by the runner management system 10. The flowchart illustrated in FIG. 5 starts at a timing when the operator inputs an instruction to execute the measurement of the tapping runner 3 to the 3D scanner 4 and then the 3D scanner 4 implements the measurement of the tapping runner 3, and the repair guidance presentation processing proceeds to the processing of Step S1.

[0032] First, in the processing of Step S1, the measurement data of the tapping runner 3 measured by the 3D scanner 4 is output from the 3D scanner 4 to the mobile information terminal 20. The measurement data includes data such as shape data of the tapping runner 3 and measurement date/time data.

[0033] Next, in the processing of Step S2, the measurement data of the tapping runner 3 is analyzed by the mobile information terminal 20. That is, the control device 201 in the mobile information terminal 20 acquires, via the communication device 203, the measurement data of the tapping runner 3 measured by the 3D scanner 4, and stores the acquired measurement data in the database of the storage device 202. Subsequently, the control device 201 reads the measurement data from the database of the storage device 202, and analyzes and extracts the cross-sectional shape of the tapping runner 3 for each of the plurality of inspection positions in the longitudinal direction of the tapping runner 3. The plurality of inspection positions are set, for example, at intervals of 1 [mm] in the longitudinal direction of the tapping runner 3.

[0034] Next, in the processing of Step S3, the measurement data of the tapping runner 3 including the cross-sectional shape of the tapping runner 3 for each of the plurality of inspection positions analyzed by the control device 201 of the mobile information terminal 20 is output to the management server 30 and stored in the database of the storage device 302. That is, the control device 301 in the management server 30 acquires, via the communication device 303, the measurement data of the tapping runner 3 including the cross-sectional shape of the tapping runner 3 for each of the plurality of inspection positions output from the mobile information terminal 20, and stores the acquired measurement data in the storage device 302. In this manner, the measurement data of the tapping runner 3 is accumulated in the database of the storage device 302 as appropriate.

[0035] Next, in the processing of Step S4, the control device 301 of the management server 30 constructs a repair guidance system based on the measurement data of the tapping runner 3 accumulated in the database of the storage device 302.

[0036] Next, in the processing of Step S5, repair guidance is presented on the display device 205 of the mobile information terminal 20 based on a determination model of the repair guidance system constructed by the control device 301 of the management server 30. That is, the control device 301 in the management server 30 outputs a predetermined determination model included in the constructed repair guidance system to the mobile information terminal 20. Subsequently, the control device 201 in the mobile information terminal 20 acquires the predetermined determination model via the communication device 203, and stores the acquired predetermined determination model in the storage device 202. Subsequently, the control device 201 functions as a determination device, and determines the wear state at each inspection position based on the measurement data of the tapping runner 3 including the cross-sectional shape of the tapping runner 3 for each of the plurality of inspection positions analyzed in the processing of Step S2 and based on the predetermined determination model. Subsequently, for example, the control device 201 presents, on the display device 205, repair guidance prompting repair of the inspection position requiring repair. This completes the processing of Step S5 to finish a series of repair guidance presentation processing.

[0037] The runner management system 10 according to the embodiment uses the 3D scanner 4 to measure the tapping runner 3. With this system, in the runner management system 10 according to the embodiment, the mobile information terminal 20 and the management server 30 can automatically record measurement data of the tapping runner 3, specify a position where the tapping runner 3 needs repair, and present repair guidance to prompt repair. With this configuration, it is possible to accurately determine the wear state of the tapping runner and to simplify the management of the necessity of repair of the tapping runner as compared with the case where the operator measures the wear state of the runner using a ruler and the operator determines the wear state of the tapping runner to manage the necessity of repair of the runner.

[0038] Next, as an example of the predetermined determination model included in the repair guidance system, a flow of learning processing of the determination model designed to determine the wear level of the tapping runner 3 will be described.

[0039] FIG. 6 is a flowchart illustrating a flow of learning processing of a determination model designed to determine a wear level. Note that, in the flowchart illustrated in FIG. 6, the control device 301 of the management server 30 functions as a computation device that obtains a determination model, and starts at a timing when an execution command of learning processing is input to the control device 301, and the learning processing proceeds to processing of Step S11.

[0040] In the processing of step S11, the operator operates the input device 304 of the management server 30 to select measurement data, as data dedicated for learning, from among pieces of measurement data of the tapping runner 3 stored in the database of the storage device 302 of the management server 30.

[0041] Next, in the processing of Step S12, the operator operates the input device 304 to classify the wear level of the tapping runner 3 in the measurement data selected in the processing of Step S11. In the present embodiment, the operator performs the classification according to the wear state of the inner wall surface 350 of the tapping runner 3 as illustrated in FIG. 7.

[0042] FIG. 7 is a diagram illustrating an example in which measurement data of the tapping runner 3 is displayed on the display device 305 of the management server 30. Reference numeral 350A in FIG. 7 represents an inner wall surface of the tapping runner 3, which is newly provided or just repaired. Reference numeral 350B in FIG. 7 represents an inner wall surface of the tapping runner 3 which has been used over time with molten iron. A position P₁ in FIG. 7 indicates a position at a depth D₁ from a position P₀ of the edge of the tapping runner 3. A position P₂ in FIG. 7 is a position deeper than the position P₁, and indicates a position at a depth D₂ (>D₁) from the position P₀ of the edge of the tapping runner 3. A width W₁ in FIG. 7 represents a width between the left and right inner wall surfaces 350A at the position P₁ in the tapping runner 3, which is newly provided or just repaired. A width W₂ in FIG. 7 represents a width between the left and right inner wall surfaces 350A at the position P₂ in the tapping runner 3, which is newly provided or just repaired. Amounts ΔW_L1 and ΔW_R1 in FIG. 7 represent left and right wear amounts at the position P₁ in the tapping runner 3 used over time. Amounts ΔWL₂ and ΔWR₂ in FIG. 7 represent left and right wear amounts at the position P₂ in the tapping runner 3 used over time.

[0043] The wear level of the inner wall surface 350 of the tapping runner 3 can be set using, for example, the left and right wear amounts ΔW_L1, ΔW_R1, ΔW_L2, and ΔW_R2 at the positions P₁ and P₂ at the depths D₁ and D₂ from the position P₀ of the edge of the tapping runner 3. In the example illustrated in FIG. 7, when the inner wall surface 350A has substantially straight shapes like the shape of the inner wall surface 350A of the runner, which is newly provided or just repaired, the wear level is set to a normal level. In contrast, as in the shape of the inner wall surface 350B used over time, a recess is formed at the positions P₁ and P₂ due to wear. Regarding the wear level in this case, the greater the recess as compared with the normal level, in other words, the larger the wear amounts ΔW_L1, ΔW_R1, ΔW_L2, and ΔW_R2, the higher the wear level is to be set stepwise.

[0044] Next, in the processing of Step S13, the control device 301 of the management server 30 performs machine learning on a determination model designed to determine the wear level, by using a set of measurement data of the tapping runner 3 as data dedicated for learning and the wear level thereof as training data, using the measurement data of the tapping runner 3 as input, and using the wear level of the tapping runner 3 as output. The machine learning method may be a known method and is not particularly limited.

[0045] Next, in the processing of Step S14, the control device 301 of the management server 30 outputs the trained determination model designed to determine the wear level, trained by machine learning in the processing of Step S13 to the storage device 302, the mobile information terminal 20, or the like. This completes the processing of Step S14 to finish a series of learning processing.

[0046] Next, as an example of the predetermined determination model included in the repair guidance system, a flow of learning processing of the determination model designed to determine the wear rate level of the tapping runner 3 will be described.

[0047] FIG. 8 is a flowchart illustrating a flow of learning processing of a determination model designed to determine a wear rate level of the tapping runner 3. Note that the flowchart illustrated in FIG. 8 starts at a timing when an execution command of the learning processing is input to the control device 301 of the management server 30, and the learning processing proceeds to the processing of Step S21.

[0048] In the processing of Step S21, the operator operates the input device 304 of the management server 30 to input data indicating the use history of the runner, being data dedicated for learning. The input data indicating the use history of the runner, being data dedicated for learning, is stored in the database of the storage device 302 of the management server 30. Examples of the data indicating the use history of the runner include various data such as temperatures, amounts, times, chemical compositions, and physical properties of molten iron and slag at various positions. Regarding the temperature and the amount, there is no need to use data directly targeted to the runner, and it is also conceivable to use a value at a position indicating a change in the temperature and the amount. In the present embodiment, data on the molten iron flow amount and the temperature of the molten iron are used as data indicating the use history of the runner.

[0049] Next, on the processing of step S22, the operator operates the input device 304 of the management server 30 to select measurement data, as data dedicated for learning, from among pieces of measurement data of the tapping runner 3 stored in the database of the storage device 302 of the management server 30.

[0050] Next, in the processing of Step S23, the operator operates the input device 304, and classifies the wear rate level of the tapping runner 3 in the data of the molten iron flow amount and the molten iron temperature of the molten iron that has been input, as data dedicated for learning, in the processing of Step S21 and the measurement data dedicated for learning selected in the processing of Step S22.

[0051] Next, in the processing of Step S24, the control device 301 of the management server 30 sets a set of data, namely, the molten iron flow amount and the molten iron temperature, being data dedicated for learning, the measurement data of the tapping runner 3 dedicated for learning, and the wear rate level thereof, as training data. Subsequently, the processing of Step S24 allows the control device 301 of the management server 30 to perform machine learning on a determination model designed to determine the wear rate level using the molten iron flow amount and the molten iron temperature as well as the measurement data of the tapping runner 3 as input and using the wear rate level of the tapping runner 3 as output. The machine learning method may be a known method and is not particularly limited.

[0052] Next, in the processing of Step S25, the control device 301 of the management server 30 outputs the trained determination model designed to determine the wear rate level of the tapping runner 3, trained by machine learning in the processing of Step S24, to the storage device 302, the mobile information terminal 20, or the like. This completes the processing of Step S25 to finish the series of learning processing.

[0053] FIG. 9 is a flowchart illustrating a flow of a determination processing of continuation of use or end of use of the tapping runner 3 performed by the runner management system 10.

[0054] First, in the processing of Step S31, the initial value of the dimension of the tapping runner 3, which is newly provided or just repaired, is measured by the 3D scanner 4 as measurement data.

[0055] Next, in the processing of Step S32, the molten iron discharged from the tap hole 2 of the blast furnace 1 is fed out to the runner, and the intermediate value of the dimension of the tapping runner 3 used over time is measured by the 3D scanner 4 as measurement data.

[0056] Next, the processing of Step S33 uses, for example, a determination model designed to determine the wear level or the wear rate level, trained with machine learning by the control device 301 of the management server 30. In the processing of Step S33, the control device 201 of the mobile information terminal 20 determines whether the tapping runner 3 is at the wear limit using the determination model, by using the measurement data of the initial value and the intermediate value of the dimension of the tapping runner 3 as input, and using the wear level or the wear rate level of the tapping runner 3 as output. When it is determined that the tapping runner 3 is not at the wear limit (No in Step S33), the processing proceeds to Step S34.

[0057] In the processing of step S34, the control device 201 of the mobile information terminal 20 refers to the data of the molten iron flow amount stored in the database of the storage device 302 of the management server 30, and determines whether the iron flow amount fed out by the tapping runner 3 is a preset reference molten iron flow amount or more. When it is determined that the molten iron flow amount is not the reference flow amount or more (No in Step S34), the processing proceeds to Step S35.

[0058] In the processing of Step S35, the control device 201 of the mobile information terminal 20 presents continuation of use of the tapping runner 3 on the display device 205. This completes the processing of Step S35, and the processing returns to the processing of Step S32.

[0059] In contrast, when it is determined in the processing of Step S33 that the tapping runner 3 is at the wear limit (Yes in Step S33), or when it is determined in the processing of Step S34 that the molten iron flow amount is the reference flow amount or more (Yes in Step S34), the processing proceeds to the processing of Step S36.

[0060] In the processing of Step S36, the control device 201 of the mobile information terminal 20 presents the end of use of the tapping runner 3 on the display device 205. This completes the processing of Step S36 to finish a series of processing of determining continuation of use or end of use of the tapping runner 3.

[0061] The runner management system 10 according to the embodiment uses the 3D scanner 4 to measure the tapping runner 3. With this configuration, it is possible, in the runner management system 10 according to the embodiment, to automatically determine and present the continuation of use or the end of use of the tapping runner 3 by the mobile information terminal 20 and the management server 30, leading to simplification of the management of the tapping runner 3.

Industrial Applicability

[0062] The present invention has been made to provide a runner management system and a runner management method capable of simplifying management of various runners (including tapping runners, slag runners, tilting runners, molten iron runners) used in conveying molten iron discharged from a tap hole of a blast furnace and accompanying slag.

Reference Signs List

[0063] 

1 BLAST FURNACE

2 TAP HOLE

3 TAPPING RUNNER

4 3D SCANNER

5 SCAFFOLDS

6 TRIPOD

7 SCALE

8 FIXTURE

9A, 9B, 9C CHECKERBOARD

10 RUNNER MANAGEMENT SYSTEM

20 MOBILE INFORMATION TERMINAL

30 MANAGEMENT SERVER

31 BACK MATERIAL

32 REFRACTORY BRICK

33 PRECAST BLOCK

34 STEEL JACKET

35 INNER LINING MATERIAL

201, 301 CONTROL DEVICE

202, 302 STORAGE DEVICE

203, 303 COMMUNICATION DEVICE

204, 304 INPUT DEVICE

205, 305 DISPLAY DEVICE

206 IMAGING DEVICE

350, 350A, 350B INNER WALL SURFACE

Claims

1. A runner management system comprising:

a measurement device disposed above a runner toward the runner and configured to measure an inner surface shape of the runner; and

a determination device configured to determine a wear state of the runner by using at least measurement data of the inner surface shape and a predetermined determination model.

2. The runner management system according to claim 1, further comprising a computation device configured to perform machine learning using a set of the measurement data dedicated for learning and the wear level of the runner as training data, using the measurement data as input, and using the wear level as output, so as to obtain a determination model designed to determine the wear level, as the predetermined determination model.

3. The runner management system according to claim 1, further comprising a computation device configured to perform machine learning using a set of data dedicated for learning and indicating a use history of the runner as well as measurement data of the inner surface shape dedicated for learning, and a wear rate level of the runner as training data, using the data indicating the use history of the runner as well as measurement data of the inner surface shape as input, and using the wear rate level as output, so as to obtain a determination model designed to determine the wear rate level, as the predetermined determination model.

4. The runner management system according to any one of claims 1 to 3, further comprising a display device configured to present continuation of use or end of use of the runner based on a determination result obtained by the determination device.

5. The runner management system according to any one of claims 1 to 3, wherein the measurement device is a 3D scanner.

6. A runner management method comprising:

a step of measuring an inner surface shape of a runner by using a measurement device disposed above the runner toward the runner; and

a step of determining a wear state of the runner by a determination device by using at least measurement data of the inner surface shape and a predetermined determination model.

7. The runner management method according to claim 6, further comprising a step of performing, by a computation device, machine learning using a set of the measurement data dedicated for learning and the wear level of the runner as training data, using the measurement data as input, and using the wear level as output, so as to obtain a determination model designed to determine the wear level, as the predetermined determination model.

8. The runner management method according to claim 6, further comprising a step of performing, by a computation device, machine learning using a set of data dedicated for learning and indicating a use history of the runner as well as measurement data dedicated for learning, and a wear rate level of the runner as training data, using the data indicating the use history of the runner as well as the measurement data as input, and using the wear rate level as output, so as to obtain a determination model designed to determine the wear rate level, as the predetermined determination model.

9. The runner management method according to any one of claims 6 to 8, further comprising a step of presenting, on a display device, continuation of use or end of use of the runner based on a determination result obtained by the determination device.

10. The runner management method according to any one of claims 6 to 8, wherein the measurement device is implemented by using a 3D scanner.

Drawing