Gutter management system and gutter management method

Abstract

To provide a gutter management system and a gutter management method which can simplify the management of a gutter.SOLUTION: A gutter management system comprises: a measurement device which is arranged above a gutter facing the gutter and measures the inner shape of the gutter; and a determination device which determines the worn state of the gutter at least using the measurement data of the inner shape and a prescribed determination model.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] The present invention relates to a gutter management system and a gutter management method. [Background technology]

[0002] Various runners (tap runners, slag runners, tilting runners, molten pig iron runners, etc.) used to transport molten pig iron discharged from the tap hole of a blast furnace and the generated slag are subject to wear and chemical reactions that cause the refractory material on the inner surface of the runner to wear out due to the high-temperature molten pig iron and slag. Furthermore, the refractory material on the inner surface of the runner is also worn out by repeated temperature increases and decreases due to factors such as switching the tap hole. Because the wear of refractory material varies depending on the situation, it is necessary to measure the inner surface shape to determine whether repairs are necessary. However, manual measurement is time-consuming and poses safety issues, as well as the problem of determining the timing of measurement. In contrast to this, Patent Document 1, for example, discloses an apparatus for measuring the inner shape of a blast furnace tap runner that enables measurement without manual labor. The apparatus comprises at least a pair of electronic distance measuring devices arranged above the blast furnace tap runner facing each other in the width direction of the blast furnace tap runner, a rotary drive device that rotates the electronic distance measuring devices in two intersecting axial directions, and a control and calculation device that controls the attitude of the electronic distance measuring devices and processes the measurement data to determine the inner shape of the blast furnace tap runner. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 09-241714 Summary of the Invention [Problem to be solved by the invention]

[0004] Although the measuring device disclosed in Patent Document 1 enables measurements without manual work, the measurement position is limited, which may result in operations that differ from past operating conditions, and if a deviation occurs in the location of wear and tear, the repair decision may not be appropriate. If an attempt is made to determine whether repairs are necessary by taking such conditions into account in the measurement data, the problem of complicated management arises.

[0005] The present invention has been made in consideration of the above-mentioned problems, and its object is to provide a trough management system and a trough management method that can simplify the management of various troughs (tapping trough, slag trough, tilting trough, molten iron trough, etc.) used to transport molten iron discharged from the tap hole of a blast furnace and generated slag. [Means for solving the problem]

[0006] In order to solve the above-mentioned problems and achieve the objectives, the gutter management system of the present invention is characterized by comprising a measuring device that is positioned above the gutter facing the gutter and measures the inner shape of the gutter, and a judgment device that judges the wear state of the gutter using at least the measurement data of the inner shape and a predetermined judgment model.

[0007] In addition, the gutter management system of the present invention is characterized in that, in the above invention, it is equipped with a computing device that performs machine learning using a pair of the measurement data for learning and the gutter wear level as learning data, the measurement data as input, and the wear level as output, and determines a judgment model for the wear level as the specified judgment model.

[0008] In addition, the gutter management system of the present invention is characterized in that, in the above invention, it is provided with a computing device that performs machine learning using a set of data indicating the usage history of the gutter for learning, measurement data of the inner surface shape for learning, and the wear rate level of the gutter as learning data, inputs the data indicating the usage history of the gutter and the measurement data of the inner surface shape, and outputs the wear rate level, and determines a judgment model of the wear rate level as the predetermined judgment model.

[0009] In addition, the gutter management system of the present invention is characterized in that, in the above invention, it is equipped with a display device that suggests whether to continue using the gutter or to end use based on the judgment result of the judgment device.

[0010] Furthermore, the gutter management system according to the present invention is characterized in that, in the above invention, the measuring device is a 3D scanner.

[0011] In addition, the gutter management method of the present invention is characterized by comprising the steps of measuring the inner shape of the gutter using a measuring device placed above the gutter facing the gutter, and judging the wear state of the gutter using a judging device using at least the measurement data of the inner shape and a predetermined judgment model.

[0012] In addition, the gutter management method of the present invention is characterized in that, in the above invention, a set of the measurement data for learning and the gutter wear level is used as learning data, and an arithmetic device performs machine learning using the measurement data as input and the wear level as output, and determines a judgment model for the wear level as the specified judgment model.

[0013] In addition, the gutter management method of the present invention is characterized in that, in the above invention, a set of data indicating the usage history of the gutter for learning, measurement data of the inner surface shape for learning, and the wear rate level of the gutter is used as learning data, and a calculation device performs machine learning using the data indicating the usage history of the gutter and the measurement data of the inner surface shape as input and the wear rate level as output, and determines a judgment model of the wear rate level as the specified judgment model.

[0014] In addition, the gutter management method of the present invention is characterized in that, in the above invention, it includes a step of displaying on a display device whether to continue using the gutter or to end use based on the judgment result of the judgment device.

[0015] Furthermore, the gutter management method according to the present invention is characterized in that, in the above invention, a 3D scanner is used as the measuring device. [Effects of the Invention]

[0016] The gutter management system and gutter management method according to the present invention have the effect of simplifying gutter management. [Brief explanation of the drawings]

[0017] [Figure 1] FIG. 1 is a diagram schematically showing a blast furnace, a tapping runner, and the like according to an embodiment. [Figure 2] FIG. 2 is a cross-sectional view showing the structure of a new tapping runner or a tapping runner immediately after repair according to the embodiment. [Figure 3] FIG. 3 is a cross-sectional view showing a worn state of the tapping runner according to the embodiment. [Figure 4] FIG. 4 is a diagram showing a schematic configuration of a gutter management system according to an embodiment. [Figure 5] FIG. 5 is a flowchart showing the flow of a gutter repair guidance presentation process performed by the gutter management system. [Figure 6] FIG. 6 is a flowchart showing the flow of the learning process for the wear level determination model. [Figure 7] FIG. 7 is a diagram showing an example of the tapping runner measurement data displayed on the display device of the management server. [Figure 8] FIG. 8 is a flowchart showing the flow of the learning process for determining the wear rate level of the gutter. [Figure 9] FIG. 9 is a flowchart showing the flow of the process of determining whether to continue or end the use of the gutter, which is carried out by the gutter management system. DETAILED DESCRIPTION OF THE INVENTION

[0018] Hereinafter, an embodiment of the blast furnace runner management method according to the present invention will be described using the case of a tapping runner as an example, although the present invention is not limited to this embodiment.

[0019] Fig. 1 is a schematic diagram showing a blast furnace 1, a tap runner 3, and the like according to an embodiment. In Fig. 1, arrow A indicates the longitudinal direction of the tap runner 3, arrow B indicates the width direction of the tap runner 3, and arrow C indicates the height direction of the blast furnace 1. As shown in Fig. 1, the tap runner 3 is disposed adjacent to a tap hole 2 provided in the blast furnace 1, and the molten iron and slag discharged from the tap hole 2 fall into the tap runner 3 while tracing a parabola.

[0020] Figure 2 is a cross-sectional view showing the structure of a new or immediately after repair tap runner 3 according to an embodiment. The tap runner 3 is constructed by pouring or spraying a lining material 35 (a monolithic refractory wear material that forms the lining layer) onto the inner surface of a refractory material called a backing material 31 that has been installed in advance in the tap runner 3. In Figure 2, reference numeral 32 denotes firebricks, reference numeral 33 denotes precast blocks, reference numeral 34 denotes a steel shell, and reference numeral 350 denotes an inner wall surface.

[0021] The inner wall surface 350 of the tap runner 3 is eroded by the molten iron and slag (slag) carried into the tap runner 3, changing from the new or immediately after repair shape shown in FIG. 2 to a shape in which the inner wall surface 350 of the tap runner 3 is worn down and recessed, as shown in FIG. 3 . Note that the molten iron and slag separate due to differences in density as they flow through the tap runner 3, and the upper side of the inner wall surface 350 of the tap runner 3 is worn down mainly by the slag, while the lower side is worn down mainly by the molten iron. Therefore, in this embodiment, the wear state of the inner wall surface 350 of the tap runner 3 is detected, and the tap runner 3 is repaired as necessary. Note that in the following description, the wear and tear state of the inner wall surface 350 of the tap runner 3 may be simply referred to as the wear and tear state of the tap runner 3.

[0022] As shown in FIG. 1 , in this embodiment, the wear state of the tap runner 3 is detected using a 3D scanner 4, which is a measuring device positioned above the tap runner 3 and facing the tap runner 3, to measure the inner shape and dimensions of the tap runner 3. While FIG. 1 shows an example in which the 3D scanner 4, which is a measuring device for measuring the inner shape and dimensions of the tap runner 3, is positioned in the longitudinal direction of the tap runner 3, the present invention is not limited thereto and the scanner may be positioned in the width direction of the tap runner 3. That is, the distance to the inner wall surface 350 of the tap runner 3 is measured at multiple points, and the wear of the inner wall surface 350 of the tap runner 3 is measured based on the measurement results. The 3D scanner 4 is a three-dimensional shape measuring device that measures the distance to each point, and can use laser, electromagnetic wave radar, ultrasonic waves, or the like. Among these, a laser-type scanner is preferred because it can set a wide measurement area and has high point-to-point resolution and distance resolution. The following explanation uses a laser-type scanner as an example.

[0023] The 3D scanner 4 is fixed to a tripod 6 installed on the floor of a scaffolding 5 suspended above the tapping lane 3 so as to be able to photograph the tapping lane 3 from the downstream side to the upstream side in the longitudinal direction. The 3D scanner 4 is able to measure the shape of the tapping lane 3 over a certain range by scanning a laser emitted toward the tapping lane 3 and measuring the distance. Note that the 3D scanner 4 can also scan a predetermined range with the laser while fixed in place by using a swing mechanism (mirror rotation) or the like to swing the laser.

[0024] Measurement of the tap runner 3 using the 3D scanner 4 is determined by comparing the state before and after wear at the same location along the length of the tap runner 3. For this purpose, as shown in FIG. 1, for example, multiple checkerboards 9A, 9B, and 9C are installed on ancillary equipment 8 fixed to the blast furnace 1 as measurement position references. The multiple checkerboards 9A, 9B, and 9C are calibration components that improve positioning accuracy by highly reflecting the laser signal from the 3D scanner 4. Using the multiple checkerboards 9A, 9B, and 9C as measurement position references allows for highly accurate comparison of measurement data, enabling highly accurate shape measurement. The multiple checkerboards 9A, 9B, and 9C are installed at intervals of 1 m or more in the width direction of the tap runner 3 (as indicated by arrow B in FIG. 1) and at intervals of 1 m or more in the height direction of the blast furnace 1 (as indicated by arrow C in FIG. 1). The checkerboards 9A, 9B, and 9C are arranged so as not to overlap one another in the height direction.

[0025] 1, a plurality of scales 7 indicating the distance from the tap hole 2 in the longitudinal direction of the tap lane 3 are provided on the edge of the tap lane 3. The plurality of scales 7 can be used as a guide for identifying the distance (position) from the tap hole 2 of the blast furnace 1 when an operator visually checks the location of wear on the tap lane 3, for example. By adopting such a method, accurate measurements can be made with just one 3D scanner 4, but multiple scanners may also be installed.

[0026] 4 is a diagram showing a schematic configuration of a gutter management system 10 according to an embodiment. The gutter management system 10 according to the embodiment is mainly composed of a 3D scanner 4, a mobile information terminal 20, and a management server 30.

[0027] The mobile information terminal 20 includes a control device 201, a storage device 202, a communication device 203, an input device 204, a display device 205, and an image capturing device 206.

[0028] The control device 201 includes, for example, a processor such as a CPU (Central Processing Unit) and memory such as a RAM (Random Access Memory) and a ROM (Read Only Memory). The control device 201 loads a program stored in the storage device 202 into a working area of ​​the memory, executes it, and controls each component device through the execution of the program, thereby realizing a function that meets a predetermined purpose.

[0029] The storage device 202 is configured from a recording medium such as a hard disk drive (HDD), etc. The storage device 202 can store an operating system (OS), various programs, various tables, various databases, etc.

[0030] The communication device 203 is configured with, for example, a wireless communication circuit for wireless communication such as Wi-Fi (registered trademark), etc. The communication device 203 communicates with the 3D scanner 4 and the management server 30 via wireless communication.

[0031] The input device 204 and the display device 205 are configured, for example, by a single touch panel display that is an input / output means. When 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 text about the wear state of the tapping lane 3. When the touch panel display functions as the display device 205, for example, text, figures, images, etc. are displayed on the screen of the touch panel display in accordance with the control of the control device 201, thereby presenting predetermined information to the outside.

[0032] The photographing device 206 includes an image sensor such as a CCD (Charge Coupled Device) image sensor or a CMOS image sensor. The photographing device 206 outputs data of the photographed image to the storage device 202. The photographing device 206 can be used, for example, when an operator photographs the state of wear and tear of the tapping runner 3 and stores the state of wear and tear of the tapping runner 3 as an image in the storage device 202 or the like.

[0033] The management server 30 includes a control device 301, a storage device 302, a communication device 303, an input device 304, a display device 305, and the like.

[0034] The control device 301 includes, for example, a processor such as a CPU, and memory such as a RAM and a ROM. The control device 301 loads a program stored in the storage device 302 into a working area of ​​the memory, executes the program, and controls each component device through the execution of the program, thereby realizing a function that meets a predetermined purpose.

[0035] The storage device 302 is configured from a recording medium such as a hard disk drive (HDD), etc. The storage device 302 can store an operating system (OS), various programs, various tables, various databases, etc.

[0036] The communication device 303 is configured with, for example, a wireless communication circuit for wireless communication such as Wi-Fi (registered trademark), etc. The communication device 303 communicates with the mobile information terminal 20 by wireless communication.

[0037] The input device 304 is configured by, for example, input means such as a keyboard and a mouse. For example, the input device 304 is configured such that predetermined information is input to the control device 301 by an operator operating the keyboard and mouse.

[0038] The display device 305 is configured by, for example, a display that is an output means, etc. The display device 305 displays characters, figures, images, etc. on the screen of the display in accordance with the control of the control device 301, for example, to present predetermined information to the outside.

[0039] The trough management system 10 according to the embodiment executes the repair guidance presentation process for the tapping trough 3 described below to accurately determine the wear state of the tapping trough 3 and manage whether or not repair of the tapping trough 3 is necessary.

[0040] Fig. 5 is a flowchart showing the flow of the repair guidance presentation process for the tapping runner 3, which is carried out by the runner management system 10. The flowchart shown in Fig. 5 starts when an operator inputs a command to the 3D scanner 4 to measure the tapping runner 3, and measurement of the tapping runner 3 is carried out by the 3D scanner 4, and the repair guidance presentation process proceeds to step S1.

[0041] First, in the process of step S1, 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 shape data of the tapping runner 3 and data on the date and time of measurement.

[0042] Next, in the processing of step S2, the measurement data of the tap runner 3 is analyzed by the mobile information terminal 20. That is, in the mobile information terminal 20, the control device 201 acquires the measurement data of the tap runner 3 measured by the 3D scanner 4 via the communication device 203 and stores the acquired measurement data in a database in the storage device 202. The control device 201 then reads the measurement data from the database in the storage device 202, and analyzes and extracts the cross-sectional shape of the tap runner 3 for each of a plurality of inspection positions in the longitudinal direction of the tap runner 3. Note that the plurality of inspection positions are set, for example, at 1 mm intervals in the longitudinal direction of the tap runner 3.

[0043] Next, in the processing of step S3, the measurement data of the tap runner 3, including the cross-sectional shape of the tap runner 3 at 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 of the management server 30 acquires the measurement data of the tap runner 3, including the cross-sectional shape of the tap runner 3 at each of the plurality of inspection positions, output from the mobile information terminal 20, via the communication device 303, and stores the acquired measurement data in the storage device 302. In this way, the measurement data of the tap runner 3 is constantly accumulated in the database of the storage device 302.

[0044] Next, in the process 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 stored in the database of the storage device 302.

[0045] Next, in the process of step S5, repair guidance is presented on the display device 205 of the mobile information terminal 20 based on the judgment model of the repair guidance system constructed by the control device 301 of the management server 30. That is, the control device 301 of the management server 30 outputs a predetermined judgment model included in the constructed repair guidance system to the mobile information terminal 20. Then, the control device 201 of the mobile information terminal 20 acquires the predetermined judgment model via the communication device 203 and stores the acquired predetermined judgment model in the storage device 202. The control device 201 then functions as a judgment device and judges 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 at each of the plurality of inspection positions analyzed in the process of step S2, and the predetermined judgment model, and presents, for example, repair guidance on the display device 205 to encourage repair for the inspection positions requiring repair. This completes the process of step S5, and the series of repair guidance presentation processes ends.

[0046] In the trough management system 10 according to the embodiment, by measuring the tapping trough 3 with the 3D scanner 4, the mobile information terminal 20 and management server 30 can automatically record the measurement data of the tapping trough 3, identify positions in the tapping trough 3 that require repair, and provide repair guidance to encourage repair. This makes it possible to determine the state of wear of the tapping trough more accurately than when an operator measures using a ruler and determines the state of wear of the tapping trough to manage whether or not the tapping trough needs repair, and also simplifies the management of whether or not the tapping trough needs repair.

[0047] Next, the flow of the learning process for a model for determining the wear level of the tapping runner 3 will be described as an example of a predetermined determination model included in the repair guidance system.

[0048] Fig. 6 is a flowchart showing the flow of the learning process for the wear level determination model. The flowchart shown in Fig. 6 starts when the control device 301 of the management server 30 functions as a calculation device that determines the determination model and a command to execute the learning process is input to the control device 301, and the learning process proceeds to step S11.

[0049] In the processing of step S11, the worker operates the input device 304 of the management server 30 to select measurement data for learning from the 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 process of step S12, the worker operates the input device 304 to classify the wear level of the tap runner 3 in the measurement data selected in the process of step S11. In this embodiment, the worker classifies the wear level according to the wear state of the inner wall surface 350 of the tap runner 3 as shown in FIG.

[0051] FIG. 7 is a diagram showing an example of the measurement data of the tap runner 3 displayed on the display device 305 of the management server 30. Reference numeral 350A in FIG. 7 represents the inner wall surface of a new tap runner 3 or a tap runner immediately after repair. Reference numeral 350B in FIG. 7 represents the inner wall surface of a tap runner 3 that has been used over time to flow molten iron. P1 in FIG. 7 represents a position at a depth D1 from the edge position P0 of the tap runner 3. P2 in FIG. 7 represents a position deeper than position P1, that is, a position at a depth D2 (>D1) from the edge position P0 of the tap runner 3. W1 in FIG. 7 represents the width between the left and right inner wall surfaces 350A at position P1 of a new tap runner 3 or a tap runner immediately after repair. W2 in FIG. 7 represents the width between the left and right inner wall surfaces 350A at position P2 of a new tap runner 3 or a tap runner immediately after repair. ΔW in FIG. 7 L1 ,ΔW R1 represents the amount of wear on the left and right at position P1 in the tap runner 3 that has been used over time. ΔWL2 and ΔWR2 in Figure 7 represent the amount of wear on the left and right at position P2 in the tap runner 3 that has been used over time.

[0052] The wear level of the inner wall surface 350 of the tapping runner 3 is, for example, the left and right wear amounts ΔW at positions P1 and P2 at depths D1 and D2 from the position P0 of the edge of the tapping runner 3. L1 ,ΔW R1 ,ΔW L2 ,ΔW R2 In the example shown in FIG. 7, when the shape of the inner wall surface 350A is almost straight, as in the case of a new surface or a surface immediately after repair, the normal level is set as the wear level. Then, as in the case of the shape of the inner wall surface 350B that has been used over time, wear has occurred at positions P1 and P2 and recesses have been formed, and the larger the recesses become compared to the normal level, in other words, the wear amount ΔW L1 ,ΔW R1 ,ΔW L2 ,ΔW R2 The more the number of items, the higher the wear level is set.

[0053] Next, in the process of step S13, the control device 301 of the management server 30 uses a set of measurement data of the tap runner 3 for learning and its wear level as learning data, and machine-learns a wear level determination model that uses the measurement data of the tap runner 3 as input and the wear level of the tap runner 3 as output. Note that the machine learning method may be any well-known method and is not particularly limited.

[0054] Next, in the process of step S14, the control device 301 of the management server 30 outputs the learned wear level determination model obtained by machine learning in the process of step S13 to the storage device 302, the mobile information terminal 20, etc. This completes the process of step S14, and the series of learning processes ends.

[0055] Next, the flow of the learning process for a judgment model for the wear rate level of the tapping runner 3 will be described as an example of a predetermined judgment model included in the repair guidance system.

[0056] Fig. 8 is a flowchart showing the flow of the learning process for the determination model of the wear rate level of the tapping runner 3. The flowchart shown in Fig. 8 starts when a command to execute the learning process is input to the control device 301 of the management server 30, and the learning process proceeds to step S21.

[0057] In the process of step S21, an operator operates the input device 304 of the management server 30 to input data indicating the usage history of the learning gutter. The input data indicating the usage history of the learning gutter is stored in a database in the storage device 302 of the management server 30. Various data can be used as data indicating the usage history of the gutter, such as the temperature, amount, time, chemical composition, and physical properties of molten iron and slag at various positions. The temperature and amount do not have to be data directly from the target gutter; it is also possible to use values ​​at positions where their changes can be seen. In this embodiment, data on the amount of molten iron passed through and the temperature of the molten iron are used as data indicating the usage history of the gutter.

[0058] Next, in the processing of step S22, the worker operates the input device 304 of the management server 30 to select measurement data for learning from the measurement data of the tapping runner 3 stored in the database of the storage device 302 of the management server 30.

[0059] Next, in the processing of step S23, the operator operates the input device 304 to classify the wear rate level of the tapping runner 3 based on the data on the amount of molten iron passed through the tapping runner 3 and the molten iron temperature data for learning input in the processing of step S21 and the measurement data for learning selected in the processing of step S22.

[0060] Next, in the processing of step S24, the control device 301 of the management server 30 uses, as learning data, a set of learning data on the amount and temperature of molten iron passed through the tap runner 3 and the wear rate level thereof, and performs machine learning to create a judgment model for the wear rate level, which uses, as input, the data on the amount and temperature of molten iron passed through the tap runner 3 and the measurement data of the tap runner 3, and outputs the wear rate level of the tap runner 3. Note that the machine learning method may be any well-known method, and is not particularly limited.

[0061] Next, in the process of step S25, the control device 301 of the management server 30 outputs the trained judgment model for the wear rate level of the tapping runner 3, which was machine-learned in the process of step S24, to the storage device 302, the mobile information terminal 20, etc. This completes the process of step S25, and the series of learning processes ends.

[0062] FIG. 9 is a flowchart showing the flow of the process performed by the trough management system 10 to determine whether to continue or end use of the tapping trough 3.

[0063] First, in the process of step S31, the initial values ​​of the dimensions of the tapping runner 3, which is new or has just been repaired, are measured by the 3D scanner 4 as measurement data.

[0064] Next, in the process of step S32, the molten iron discharged from the tap hole 2 of the blast furnace 1 is carried out, and the intermediate values ​​of the dimensions of the tap runner 3 that has been used over time are measured by the 3D scanner 4 as measurement data.

[0065] Next, in the processing of step S33, for example, using a determination model for the wear level or wear rate level learned by machine learning by the control device 301 of the management server 30, the control device 201 of the mobile information terminal 20 inputs measurement data of the initial and intermediate dimensions of the tap runner 3 and outputs the wear level or wear rate level of the tap runner 3 to determine whether the tap runner 3 is at the wear limit. Then, if it is determined that the tap runner 3 is not at the wear limit (No in step S33), the process proceeds to step S34.

[0066] In the processing of step S34, the control device 201 of the mobile information terminal 20 refers to the data on the amount of molten iron passed through the tapping runner 3, stored in the database of the storage device 302 of the management server 30, and determines whether the amount of molten iron passed through the tapping runner 3 is equal to or greater than a predetermined reference amount of passed iron. If it is determined that the amount is not equal to or greater than the reference amount of passed iron (No in step S34), the processing proceeds to step S35.

[0067] In the process of step S35, the control device 201 of the mobile information terminal 20 displays on the display device 205 the continuation of use of the tapping runner 3. This completes the process of step S35, and the process returns to the process of step S32.

[0068] On the other hand, if it is determined in the processing of step S33 that the tapping runner 3 is at its wear limit (Yes in step S33), or if it is determined in the processing of step S34 that the amount of passing iron is equal to or greater than the standard amount of passing iron (Yes in step S34), the processing proceeds to step S36.

[0069] In the processing of step S36, the control device 201 of the mobile information terminal 20 displays on the display device 205 the end of use of the tapping runner 3. This completes the processing of step S36, and the series of processes for determining whether to continue using the tapping runner 3 or to end its use is terminated.

[0070] In the gutter management system 10 of the embodiment, by measuring the iron tapping gutter 3 using a 3D scanner 4, the mobile information terminal 20 and management server 30 can automatically determine whether to continue using the iron tapping gutter 3 or to end its use and present the result, thereby simplifying the management of the iron tapping gutter 3. [Explanation of symbols]

[0071] 1 blast furnace 2 Taphole 3 Tapping sluice 4. 3D scanner 5. Scaffolding 6. Tripod 7 scales 8. Ancillary Facilities 9A, 9B, 9C Checkerboard 10 Gutter Management System 20. Mobile Information Terminals 30 Management Server 31 Back material 32 Firebrick 33 Precast Blocks 34 Ironhide 35 Lining material 201,301 Control device 202,302 Storage device 203,303 Communication equipment 204,304 Input devices 205,305 Display device 206 Imaging Device 350, 350A, 350B inner wall surface

Claims

1. a measuring device disposed above the tapping runner facing the tapping runner and configured to measure the inner surface shape of the tapping runner; a determination device that determines the state of wear of the tap runner by comparing a state before wear and a state after wear at the same location in the longitudinal direction of the tap runner using at least the measurement data of the inner surface shape and a predetermined determination model; Equipped with the predetermined judgment model is a judgment model for a wear level of the tapping runner or a judgment model for a wear rate level of the tapping runner, the measuring device measures, as the measurement data, an initial value of the dimension of the tap runner, representing a state before the tap runner is worn, and measures, as the measurement data, an intermediate value of the dimension of the tap runner, representing a state after the tap runner is worn; the determination device receives the measurement data of the initial value and the intermediate value as an input, and outputs the wear level or the wear rate level to determine whether the tapping runner is at the wear limit. A gutter management system characterized by:

2. The gutter management system according to claim 1, characterized in that it comprises a computing device that performs machine learning using a set of the measurement data for learning and the wear level of the tapping gutter as learning data, with the measurement data as input and the wear level as output, and determines a judgment model for the wear level as the specified judgment model.

3. The gutter management system according to claim 1, characterized in that it comprises a computing device that performs machine learning using a set of data indicating the usage history of the tap runner for learning, measurement data of the inner surface shape for learning, and a wear rate level of the tap runner as learning data, inputs the data indicating the usage history of the tap runner and the measurement data of the inner surface shape, and outputs the wear rate level, and determines a judgment model for the wear rate level as the specified judgment model.

4. 4. The trough management system according to claim 1, further comprising a display device that indicates whether to continue using the tapping trough or to end its use based on the determination result of the determination device.

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

6. a step of measuring an inner surface shape of the tapping runner using a measuring device disposed above the tapping runner and facing the tapping runner; determining the state of wear of the tap runner by a determination device by comparing the state before wear and the state after wear at the same location in the longitudinal direction of the tap runner using at least the measurement data of the inner surface shape and a predetermined determination model; and the predetermined judgment model is a judgment model for a wear level of the tapping runner or a judgment model for a wear rate level of the tapping runner, the measuring device measures, as the measurement data, an initial value of the dimension of the tap runner, representing a state before the tap runner is worn, and measures, as the measurement data, an intermediate value of the dimension of the tap runner, representing a state after the tap runner is worn; the determination device receives the measurement data of the initial value and the intermediate value as an input, and outputs the wear level or the wear rate level to determine whether the tapping runner is at the wear limit. A gutter management method characterized by:

7. The trough management method according to claim 6, characterized in that it includes a process in which a calculation device performs machine learning using a set of the measurement data for learning and the wear level of the tap trough as learning data, the measurement data as input, and the wear level as output, and determines a judgment model for the wear level as the predetermined judgment model.

8. The method for managing the tap runner according to claim 6, characterized in that it comprises a process in which a computing device performs machine learning using a set of data indicating the usage history of the tap runner for learning, the measurement data for learning, and the wear rate level of the tap runner as learning data, with the data indicating the usage history of the tap runner and the measurement data as inputs and the wear rate level as output, to determine a judgment model for the wear rate level as the predetermined judgment model.

9. 9. The method for managing the tapping lane according to claim 6, further comprising a step of displaying on a display device whether to continue or terminate use of the tapping lane based on the determination result of the determination device.

10. The gutter management method according to any one of claims 6 to 8, characterized in that a 3D scanner is used as the measuring device.

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