Drum-type magnetic separator, system for removing unsuitable materials for crushing, and method for separating unsuitable materials for crushing

Abstract

To enable crushing unsuitable matters having a possibility of breaking shredder equipment from in an individual old waste scrap with high accuracy in a preliminary step of inputting the old waste scrap into a shredder.SOLUTION: A crushing unsuitable matter removal system for removing a crushing unsuitable matter having a possibility of damaging shedder equipment in a preliminary step for inputting a scrap into the shedder equipment for breaking the scrap includes a drum type magnetic separator for removing magnetic matters equal to or more than prescribed weight in the scrap, an imaging device for photographing the scrap from which the magnetic matters equal to or more than the prescribed weight are removed by the drum type magnetic separator, and an information processing device for acquiring and analyzing a photographed image from the imaging device, and the information processing device specifies the crushing unsuitable matters from a picked-up image by using a learning model for specifying the crushing unsuitable matters, and outputs the effect that the crushing unsuitable matters included in the scrap when the crushing unsuitable matters are specified.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a technology suitable for use in pre-removing scrap that may damage shredder equipment. This application claims priority to Japanese Patent Application No. 2022-186360, filed on November 22, 2022, the contents of which are incorporated herein by reference. [Background technology]

[0002] In recent years, there has been a growing need to reduce CO2 emissions to curb global warming, and in the steel industry, the electric furnace method has been attracting attention as an alternative to the blast furnace method, which emits CO2 gas. The electric furnace method primarily uses scrap iron, which is made from used steel products such as discarded automobiles, discarded home appliances, buildings, and other used steel products, as its main raw material. However, scrap iron, discarded automobiles, discarded home appliances, buildings, and other used steel products contain various metals and non-metals in addition to iron. Therefore, when shredding scrap (hereinafter referred to as "waste scrap") generated from used steel products and other waste materials in a shredder facility, it is common to separate the iron from other metals and non-metals.

[0003] When discarded scrap is fed into the shredder equipment, if any items that are not suitable for shredding, such as pressure vessels like gas cylinders that pose a risk of explosion, or large iron blocks like motors or structural steel, are fed in, they could damage the shredder equipment, so it is necessary to remove these items beforehand before feeding them into the shredder equipment.

[0004] Conventionally, when removing materials unsuitable for shredding before feeding them into shredder facilities, workers would operate heavy machinery and visually select and remove the materials. However, because workers had to sort through a huge amount of obsolete scrap, removal work by hand resulted in low removal efficiency due to oversights and mis-sorting, and frequent explosions and other problems inside the shredder facilities. Therefore, various technologies have been proposed to remove materials unsuitable for shredding.

[0005] Patent Document 1 discloses a method in which a monitoring camera detects unsuitable materials for shredding, and a discharge section is provided at the inlet side of the shredder to drop them and discharge them outside the shredding system. Patent Document 2 also discloses a method in which X-ray fluoroscopic images are used to automatically detect unsuitable materials for shredding, and the waste input device is automatically stopped and the materials are removed by an unsuitable material removal device.

[0006] However, the method described in Patent Document 1 is a technology in which a monitor visually checks the surveillance camera footage and, if any objects unsuitable for shredding are included in the footage, removes the objects outside the shredding system, so there is still a possibility of oversights, erroneous sorting, etc. Furthermore, the method described in Patent Document 2 is a system in which an object is determined to be unsuitable for shredding if a series of pixels with a density above a predetermined level occupy a predetermined area or more in an X-ray fluoroscopic image, so the detection accuracy is insufficient and there is still a possibility of oversights, erroneous sorting, etc. [Prior art documents] [Patent documents]

[0007] [Patent Document 1] Japanese Patent Publication No. 2011-92902 [Patent Document 2] Japanese Patent Publication No. 8-309277 [Patent Document 3] Japanese Patent Publication No. 2005-144390 [Non-patent literature]

[0008] [Non-Patent Document 1] Joseph Redmon, 3 others, "You Only Look Once: Unified, Real-Time Object Detection" [Retrieved May 18, 2021], Internet <https: / / arxiv.org / abs / 1506.02640> [Non-patent document 2] Olaf Ronneberger and two others, "U-Net: Convolutional Networks for Biomedical Image Segmentation" (Retrieved May 18, 2021), Internet <URL: https: / / arxiv.org / abs / 1505.04597> [Non-patent document 3] Samet Akcay, 2 others, "GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training" [Retrieved May 18, 2021], Internet <https: / / arxiv.org / abs / 1805.06725> [Non-patent document 4] Paul Bergmann, 3 others, "Improving Unsupervised Defect Segmentation by Applying Structural Similarity to Autoencoders", [Retrieved May 18, 2021], Internet <https: / / arxiv.org / abs / 1807.02011> [Non-patent document 5] Paolo Napoletano, 2 others, "Anomaly Detection in Nanofibrous Materials by CNN-Based Self-Similarity", [Retrieved May 18, 2021], Internet <https: / / www.ncbi.nlm.nih.gov / pmc / articles / PMC5795842 / > Summary of the Invention [Problem to be solved by the invention]

[0009] In view of the above-mentioned problems, the present invention aims to accurately remove from individual obsolete scraps materials that are unsuitable for shredding and that may damage the shredder equipment, before the obsolete scraps are fed into the shredder equipment. [Means for solving the problem]

[0010] The drum-type magnetic separator according to the present invention is a component of a system for removing unsuitable materials for shredding that may cause damage to shredder equipment before the scrap is fed into the shredder equipment, and has a magnetic force set to attract magnetic materials of less than a predetermined weight among the scrap, and is also connected to a vibrating feeder that transports the scrap. the tip of the drum-type magnetic separator The distance between the Another feature of the drum-type magnetic separator according to the present invention is that it is a drum-type magnetic separator that constitutes a system for removing unsuitable materials for shredding, which removes materials unsuitable for shredding that may cause damage to shredder equipment before the scrap is fed into the shredder equipment, and The distance between the tip of the vibrating feeder that transports the scrap and the drum-type magnetic separator is adjustable, Among the scrap, magnetic material having a predetermined weight or more is separated from the drum-type magnetic separator. Record The magnetic force of the magnets of the drum-type magnetic separator is set so that magnetic objects of less than a predetermined weight are attracted and adsorbed to the rotating drum so as to fall through the gap between the rotating drum and the rotary feeder, and so that the magnetic objects are not allowed to fall into the gap, and the magnetic objects attracted by the magnetic force of the magnets are separated from the rotating drum by being moved out of the magnetic force range of the magnets as the rotating drum rotates. Another feature of the drum-type magnetic separator according to the present invention is that it is a drum-type magnetic separator that constitutes a system for removing unsuitable materials for shredding, which removes materials unsuitable for shredding that may cause damage to shredder equipment before the scrap is fed into the shredder equipment, and The height of the vibration feeder that conveys the scrap is at the same level as or lower than the height of the rotary drum, the magnetic force of the magnet of the drum-type magnetic separator is set so that magnetic materials of the scrap that are less than a predetermined weight are attracted to the rotating drum; From the vibrating feeder The magnetic material attracted by the magnetic force of the magnet is removed from the magnetic field of the magnet by the rotation of the rotary drum, and the magnetic material having a weight equal to or greater than the predetermined weight is separated from the rotary drum. From the vibrating feederThe magnetic object is placed on the rotating drum, and the magnetic object having a weight equal to or greater than the predetermined weight is allowed to fall by gravity before it leaves the magnetic field of the magnet due to the rotation of the rotating drum. The system for removing materials unsuitable for shredding of the present invention is a system for removing materials unsuitable for shredding that may cause damage to shredder equipment before scrap is fed into the shredder equipment that shreds the scrap, and is characterized by comprising: an information processing device that includes an identification means for identifying magnetic materials unsuitable for shredding based on at least one of photographed images and three-dimensional shape measurement results of the magnetic materials in the scrap, and an output means that, if an material unsuitable for shredding is identified by the identification means, outputs a message indicating that the scrap contains materials unsuitable for shredding; and a drum-type magnetic separator whose magnetic force is set to attract magnetic materials of less than a predetermined weight from the scrap excluding the materials unsuitable for shredding identified by the identification means.

[0011] The method for separating materials unsuitable for shredding according to the present invention is a method for separating materials unsuitable for shredding that uses a drum-type magnetic separator that constitutes an unsuitable for shredding removal system that removes materials unsuitable for shredding that may cause damage to shredder equipment before the scrap is fed into the shredder equipment, and is characterized by comprising a step of adjusting the distance from a vibrating feeder that transports the scrap so as to attract and separate magnetic materials of less than a predetermined weight from the scrap. In addition, the method for separating materials unsuitable for crushing according to the present invention includes the steps of: This is a method for separating materials unsuitable for shredding in an unsuitable for shredding removal system that removes materials unsuitable for shredding that may cause damage to shredder equipment before scrap is fed into the shredder equipment that shreds the scrap, and is characterized by comprising: a first step of identifying magnetic materials unsuitable for shredding based on at least one of photographed images and three-dimensional shape measurement results of the magnetic materials in the scrap, thereby removing the magnetic materials unsuitable for shredding; and a second step of using a drum-type magnetic separator to attract and separate magnetic materials less than a predetermined weight from the scrap excluding the unsuitable for shredding materials identified in the first step. [Effects of the Invention]

[0012] According to the present invention, before the obsolete scrap is fed into the shredder equipment, it is possible to accurately remove from each obsolete scrap any material that is unsuitable for shredding and that may damage the shredder equipment. [Brief explanation of the drawings]

[0013] [Figure 1] FIG. 1 is a diagram illustrating an outline of a system for removing objects unsuitable for crushing in an embodiment of the present invention. [Figure 2] FIG. 2 is a block diagram showing an example of the functional configuration of an information processing device that detects objects unsuitable for crushing in an embodiment of the present invention. [Figure 3] FIG. 3 is a block diagram showing an example of the hardware configuration of an information processing device that detects objects unsuitable for crushing in an embodiment of the present invention. [Figure 4] FIG. 4 is a flowchart showing an example of a processing procedure for detecting objects unsuitable for crushing using a learning model by an information processing device in the first embodiment of the present invention. [Figure 5]FIG. 5 is a diagram for explaining an outline of a drum-type magnetic separator that discharges materials unsuitable for shredding outside the system in the first embodiment of the present invention. [Figure 6A] FIG. 6A is a diagram showing an example of an image captured by a surveillance camera and a learning image clearly showing objects unsuitable for crushing. [Figure 6B] FIG. 6B is a diagram showing another example of an image captured by a surveillance camera and a learning image clearly showing objects unsuitable for crushing. [Figure 6C] FIG. 6C is a diagram showing another example of an image captured by a surveillance camera and a learning image clearly showing objects unsuitable for crushing. [Figure 7A] FIG. 7A is a diagram showing an example of a display screen when an object unsuitable for crushing is detected. [Figure 7B] FIG. 7B is a diagram showing another example of the display screen when an object unsuitable for crushing is detected. [Figure 8] FIG. 8 is a diagram illustrating an overview of an overfeed type drum-type magnetic separator that discharges materials unsuitable for shredding outside the system in a second embodiment of the present invention. [Figure 9] FIG. 9 is a diagram for explaining an outline of removing materials unsuitable for crushing that have been transported onto the second vibrating feeder in the third embodiment of the present invention. [Figure 10A] FIG. 10A is a diagram showing a specific example of basic shape information. [Figure 10B] FIG. 10B is a diagram showing a specific example of an image in which edges extracted from a two-dimensional image are shown. [Figure 10C] FIG. 10C is a diagram showing a specific example of an image in which a surface extracted from a two-dimensional image is shown. [Figure 11A] FIG. 11A is a diagram showing a specific example of point cloud data. [Figure 11B] FIG. 11B is a diagram showing a specific example of an edge extracted from point cloud data. [Figure 11C] FIG. 11C is a diagram showing a specific example of a surface extracted from point cloud data. [Figure 12A] FIG. 12A is a diagram for explaining a method for identifying a surface to be noted in a shape such as a half-split steel pipe. [Figure 12B] FIG. 12B is a diagram for explaining another method for identifying a surface to be noted in a shape such as a half-split steel pipe. DETAILED DESCRIPTION OF THE INVENTION

[0014] The following describes an embodiment of the present invention with reference to the drawings. In the following description, unsuitable materials for shredding are materials that may damage shredder equipment, such as pressure vessels such as gas cylinders that pose a risk of explosion, and large iron blocks such as motors and structural steel.

[0015] (First embodiment) [System Configuration] FIG. 1 is a diagram for explaining an outline of an unsuitable crushing object removal system 100 for removing unsuitable crushing objects in this embodiment. As shown in FIG. 1, in the shredded material removal system 100 according to this embodiment, an operator first uses heavy machinery to feed obsolete scrap into a pre-shredder 1 for coarse shredding. The coarsely shredded obsolete scrap is then transported onto a first vibrating feeder 2. The coarsely shredded obsolete scrap may contain materials unsuitable for shredding, but at least some of these materials are removed from the system by a drum-type magnetic separator 3. Meanwhile, the obsolete scrap collected by the drum-type magnetic separator 3 is transported onto a second vibrating feeder 4 and photographed by a monitoring camera 5 located midway along the second vibrating feeder 4. If any materials unsuitable for shredding that were not removed by the drum-type magnetic separator 3 are detected in the image from the monitoring camera 5, the materials are removed using a robot arm (not shown) or the like. Each piece of equipment is described in detail below.

[0016] Pre-shredder 1 has two or three rotors, and the bladed rotors rotate at a low speed to roughly shred the waste scrap that has been fed into it, such as in a pressed, compressed state. When waste scrap is fed into pre-shredder 1, it processes the waste scrap into a shape that can be crushed. Note that because pre-shredder 1 is a coarse-shredding facility, the gaps between the rotors are larger than those of a normal shredder, making it easier for materials that are not suitable for shredding to slip through. Furthermore, materials larger than the gaps between the rotors cannot be coarse-shredded, and the rotors will stop due to an overload trip. The roughly shredded waste scrap is then dropped onto first vibrating feeder 2.

[0017] The first vibrating feeder 2 is a vibrating feeder for supplying waste scrap to the drum-type magnetic separator 3, and by vibrating the waste scrap 6 that is piled up when placed on the conveyor, it spreads the waste scrap 6 over the entire conveyor while transporting it, improving the accuracy of magnetic separation by the drum-type magnetic separator 3.

[0018] The drum-type magnetic separator 3 has a magnet mounted inside the drum, and collects iron attracted to the magnet as the outside of the drum rotates. Here, the drum-type magnetic separator 3 will be described in detail with reference to FIG. 5.

[0019] As shown in FIG. 5 , the drum-type magnetic separator 3 rotates a rotating drum 33 equipped with an electromagnet 32 ​​around a drum shaft 31. This attracts and collects thin and lightweight crushed materials 6a (magnetic materials) from the waste scrap 6. Meanwhile, non-magnetic materials 6c (non-ferrous metals, plastics, rubber, dust, etc.) that cannot be attracted by the magnetic force of the electromagnet 32 ​​are discharged outside the system. Furthermore, because the waste scrap 6 transported by the first vibrating feeder 2 is roughly crushed, unlike conventional magnetic separators, the drum-type magnetic separator 3 also transports thick and heavy materials 6b that are unsuitable for shredding. In this embodiment, the crushed materials 6a and the unsuitable for shredding materials 6b are separated and discharged by appropriately adjusting at least one of the distance between the tip of the first vibrating feeder 2 and the drum-type magnetic separator 3, the magnetic force of the electromagnet 32, and the rotational speed of the rotating drum 33.

[0020] The electromagnet 32 ​​does not rotate. The crushed materials 6a attracted to the rotating drum 33 by the electromagnet 32 ​​move as the rotating drum 33 rotates, and once they leave the magnetic field of the electromagnet 32, they move forward due to inertial force. The crushed materials 6a then fall by gravity onto the second vibrating feeder 4, where they are separated from the drum-type magnetic separator 3. However, this is not limited to the present embodiment. The crushed materials 6a that leave the electromagnet 32 ​​may be collected, transported to the second vibrating feeder 4 by hand or by a transport vehicle, and then placed on the second vibrating feeder 4. Furthermore, the surface of the rotating drum 33 may be provided with a plurality of radially extending plate-like members along the circumferential direction, which can support magnetic materials that slide during rotation even outside the magnetic field of the electromagnet 32 ​​and forcibly transport them in the direction of rotation. The electromagnet 32 ​​may have any shape and any position on the rotating drum 33, as long as it can attract and separate the crushed materials 6a as described above.

[0021] Increasing the distance between the tip of the first vibrating feeder 2 and the drum-type magnetic separator 3 reduces the effect of magnetic force, while increasing the rotational speed of the rotating drum 33 increases the conveyance volume. Furthermore, if the magnetic force of the electromagnet 32 ​​is too strong, thick or heavy objects will be attracted to the rotating drum 33, so the magnetic force of the electromagnet 32 ​​is adjusted according to the weight and size of the objects, which could potentially damage the shredder equipment. By adjusting the distance between the tip of the first vibrating feeder 2 and the drum-type magnetic separator 3, the rotational speed of the rotating drum 33, and the magnetic force of the electromagnet 32, objects unsuitable for shredding exceeding a certain weight cannot be collected by magnetic force, allowing thick or heavy objects to be discharged from the system. When adjusting the rotational speed of the rotating drum 33, it is preferable to also adjust the conveyance speed of the first vibrating feeder 2. On the other hand, scrap containing hollow objects such as gas cylinders and scrap containing light metals such as aluminum in addition to iron has a small weight relative to its volume, and therefore may be collected as crushed material despite its large volume. The scrap collected by the drum-type magnetic separator 3 is dropped into the second vibrating feeder 4. In this embodiment, magnetic objects of a certain weight or more are considered to be difficult to attract to the rotating drum 33 by the magnetic force of the electromagnet 32, while magnetic objects of a weight less than the certain weight are considered to be easily attracted to the rotating drum 33 by the magnetic force of the electromagnet 32.

[0022] More specifically, for example, The tip of the first vibrating feeder 2 and The magnetic force of the drum type magnetic separator 3 may be set so as to attract magnetic materials of less than a predetermined weight, taking into consideration the distance from the drum type magnetic separator 3 and the rotation speed of the rotating drum 33. For example, the magnetic force may be adjusted by adjusting the value of the current flowing through the electromagnet. After the magnetic force of the drum type magnetic separator 3 is determined, The tip of the first vibrating feeder 2 andAt least one of the distance from the drum type magnetic separator 3 and the rotation speed of the rotating drum 33 may be adjusted so that magnetic materials of less than a predetermined weight are attracted to the electromagnet 32 ​​of the drum type magnetic separator 3. When the magnetic force of the drum type magnetic separator 3 is fixed, a permanent magnet may be used as the magnet. This also applies to the overfeed type drum type magnetic separator 80 described later.

[0023] Like the first vibrating feeder 2, the second vibrating feeder 4 conveys the piled obsolete scrap 7 by vibrating it to spread it across the entire conveyor. The surveillance camera 5 captures the obsolete scrap being conveyed from above in a section of the second vibrating feeder 4. If vibrations from the second vibrating feeder 4 occur in the area captured by the surveillance camera 5, the captured image will be blurred. Therefore, it is preferable to spread the piled obsolete scrap 7 across the entire conveyor before it reaches the area captured by the surveillance camera 5, so that vibrations from the second vibrating feeder 4 are not generated in the area captured by the surveillance camera 5. From this perspective, a separate, non-vibrating, general belt conveyor may be installed downstream of the second vibrating feeder 4, and the obsolete scrap 7 on that belt conveyor may be captured by the surveillance camera 5.

[0024] The surveillance camera 5 captures images of the obsolete scrap being transported from above, either directly below or at an angle, and sequentially transfers the captured images to the information processing device 10 in real time. The information processing device 10 detects objects unsuitable for shredding from the captured images and notifies the supervisor when such objects are detected. The method for detecting objects unsuitable for shredding will be described later. Furthermore, to supplement the height information of obsolete scrap within the surveillance camera 5's field of view, a three-dimensional shape measuring device 8 also measures the shape of the obsolete scrap in parallel. The shape measurement results are also transferred to the information processing device 10 and used to determine whether or not any objects unsuitable for shredding are present. The three-dimensional shape measuring device 8 may be, for example, a time-of-flight (ToF) camera or a laser scanner.

[0025] 1, there is only one monitoring camera 5, but to further improve the detection accuracy of objects unsuitable for shredding, multiple cameras may be arranged in the width direction or conveyance direction. Also, in some cases, such as with gas cylinders, height information can be predicted to a certain extent, so shape measurement by the three-dimensional shape measuring device 8 may be omitted in order to simplify the unsuitable for shredding object removal system 100.

[0026] Once the materials unsuitable for shredding have been removed from the second vibrating feeder 4, the shredded materials are collected and transported to a shredder facility (not shown). The shredder facility is well known (see, for example, Patent Document 1), and after the materials are further pulverized by a shredder, a magnetic separator separates the materials into magnetic materials such as iron and non-magnetic metals.

[0027] [Configuration of information processing device] Next, a detailed description will be given of the procedure for detecting objects unsuitable for crushing using the monitoring camera 5. Fig. 3 is a block diagram showing an example of the hardware configuration of an information processing device 10 that detects objects unsuitable for crushing in this embodiment. As shown in FIG. 3, the information processing device 10 includes a CPU 301, a ROM 302, a RAM 303, a storage device 304, an input / output I / F 305, and a communication I / F 306, which are connected by a bus 307.

[0028] The CPU 301 reads out control programs stored in the ROM 302 or the storage device 304 and executes various processes. The RAM 303 is used as a temporary storage area such as the main memory or work area of ​​the CPU 301. The storage device 304 stores various data, programs, etc. The input / output I / F 305 is an interface for accepting various operations by the user via the keyboard or mouse and displaying calculation results on a display device (not shown).

[0029] The communication I / F 306 is an interface for acquiring information from an external device via a network, etc. Images of obsolete scrap captured by the monitoring camera 5 are received by the information processing device 10 of this embodiment via the communication I / F 306 by wired or wireless communication. The measurement results of the three-dimensional shape measuring device 8 are also received by the information processing device 10 of this embodiment via the communication I / F 306 by wired or wireless communication.

[0030] Fig. 2 is a block diagram showing an example of the functional configuration of the information processing device 10 according to this embodiment. Note that each component shown in Fig. 2 is realized by the CPU 301 reading and executing a control program stored in the ROM 302 or the storage device 304. Each component will be described below.

[0031] The image acquisition unit 201 acquires the images captured by the monitoring camera 5 as a video or one or more still images. The captured images are of the obsolete scrap being transported by the second vibrating feeder 4, as described above, and the angle of view of the monitoring camera 5 is set to match the width of the obsolete scrap on the second vibrating feeder 4. Therefore, the monitoring camera 5 can capture images so that the obsolete scrap is included in the entire captured image.

[0032] The unsuitable object identification unit 202 inputs the captured image acquired by the image acquisition unit 201 into a learning model (a learning model that has been trained by machine learning) to identify candidates for unsuitable objects for shredding and their locations within the captured image. Here, the learning model is a model that has been trained to identify unsuitable objects for shredding from images, and details will be described later. Note that unsuitable objects for shredding include magnetic objects equivalent to thin and lightweight objects (for example, gas cylinders with many cavities), as well as thick or heavy objects that failed to be separated by the drum-type magnetic separator 3.

[0033] The volume calculation unit 206 inputs the measurement results from the three-dimensional shape measurement device 8 and calculates the volume of each obsolete scrap based on the measurement results. Since the purpose of this embodiment is to identify obsolete scrap that is unsuitable for shredding, volume calculation may be omitted for obsolete scrap that is clearly not unsuitable for shredding based on the three-dimensional shape measurement results. For example, the volume may be calculated only for obsolete scrap whose height is equal to or greater than a predetermined value or whose surface area is equal to or greater than a predetermined value. Furthermore, because the three-dimensional shape measurement is intended to supplement the height information of candidates for obsolete scrap identified by the learning model, it is also possible to calculate only the height of each obsolete scrap without calculating the volume. While calculating only the height may result in lower accuracy in identifying whether or not an item is unsuitable for shredding compared to calculating the volume, the reduced computational effort shortens the time required to identify whether or not an item is unsuitable for shredding.

[0034] The determination unit 207 determines whether the candidate for unsuitable material for shredding is actually unsuitable material for shredding based on the candidate for unsuitable material identified by the unsuitable material identification unit 202 and the volume of obsolete scrap calculated by the volume calculation unit 206. It is possible that an object is not identified as an unsuitable material for shredding when viewed vertically by the learning model, but its height exceeds a predetermined value and its volume corresponds to that of an object unsuitable for shredding. However, because the second vibrating feeder 4 vibrates the obsolete scrap so that the pile is flat when transported, this case is unlikely to occur.

[0035] If the determination unit 207 determines that an object unsuitable for shredding is included, the result output unit 208 notifies the user of this fact. The notification method is not particularly limited, and any method may be used as long as the worker can visually identify the object unsuitable for shredding and remove it. For example, as shown in FIG. 7A , an image of the object unsuitable for shredding 701 in the captured image surrounded by a rectangle 702 may be displayed on a display device (not shown), along with a warning message 703. Alternatively, as shown in FIG. 7B , a superimposed image may be generated in which the object unsuitable for shredding 701 is marked, and the superimposed image and warning message 703 may be displayed on a display device (not shown). Alternatively, the location of the object unsuitable for shredding may be notified via an audio speaker (not shown). In this manner, the worker operating the robot arm or the like can identify the location of the object unsuitable for shredding and remove it. The robot arm or the like does not need to be operated by a worker and may be automated. In this case, the determination result that an object unsuitable for crushing is contained may be output directly to the robot arm or the like, as well as information relating to the location of the object.

[0036] Next, the learning model will be described in detail. The learning model is, for example, a trained model generated by deep learning such as a neural network. As a deep learning method, a multi-layer neural network such as a convolutional neural network (CNN) can be applied, but is not limited to this.

[0037] The model generation unit 203 generates one or more learning models that identify the location of objects unsuitable for shredding and the probability that they are unsuitable for shredding from images captured by the surveillance camera 5. Specifically, using a plurality of data sets associated with images of obsolete scrap, such as that shown in FIG. 6A, and information indicating the type and location of objects unsuitable for shredding (gas cylinders in the case of FIGS. 6A-6C) 601 contained in the images as learning data, the model generation unit 203 generates a model that identifies the type, location, and probability that the objects are unsuitable for shredding in the images through machine learning. For example, a learning model that outputs the type, location, and probability of an object being an object, as shown in Non-Patent Documents 1 and 2, may be generated. Note that the types of objects unsuitable for shredding may be classified into multiple types, such as "gas cylinders" and "structural steel," and output, or simply output as a single type, "object unsuitable for shredding."

[0038] The learning data is stored in advance in the data storage unit 205, and in this embodiment, a set of learning data is used consisting of past images captured by the monitoring camera 5 and label data that can identify the correct area in the image where objects unsuitable for crushing exist. For example, an image in which areas where objects unsuitable for crushing exist are manually determined in advance in a past captured image, and all of the objects unsuitable for crushing are labeled (marked) is used as a set of learning data.

[0039] The past captured images used as learning data are preferably images captured by the same camera as the images used to detect objects unsuitable for shredding by the unsuitable object identification unit 202, but may be images captured by a different camera. Furthermore, the images used as learning data are preferably images obtained by capturing actual objects unsuitable for shredding mixed in with obsolete scrap, but may also be images of objects unsuitable for shredding available via the internet (such as images of gas cylinders). During learning, an optimization objective function is set so that the probability that an object is unsuitable for shredding is equal to or greater than a predetermined reference value (e.g., 100%) for manually generated correct label data.

[0040] The label data used here may be marking image data in which the positions of the objects 601 unsuitable for shredding are marked in the captured image, as shown in FIG. 6C. In this case, brightness values ​​previously assigned to each object unsuitable for shredding can be used as information representing the type of the marked object unsuitable for shredding. For example, when a grayscale image expressed in brightness values ​​ranging from 0 to 255 is used as the marking image, the type of object unsuitable for shredding can be distinguished by the brightness value of each pixel, for example, by marking gas cylinders with a brightness of 100 and structural steel with a brightness of 50. Of course, the coordinates of multiple pixels having brightness values ​​assigned as objects unsuitable for shredding can be used as information representing the positions of the marked object unsuitable for shredding.

[0041] 6B, the label data may be text data including rectangle information 602 created to surround the object unsuitable for crushing in the captured image. For example, this text data may use rectangular coordinate data as the position of the object unsuitable for crushing, and information that can identify the object unsuitable for crushing within the rectangle as the type of object unsuitable for crushing. The captured image data used above may be in a format such as jpg, bmp, or png, and the text data may be in a format such as txt, json, or xml.

[0042] Alternatively, the model generation unit 203 may generate a learning model that learns normal images and detects deviations from normality as an anomaly, as described in Non-Patent Documents 3-5. In this method, multiple images of normal obsolete scrap that do not contain objects unsuitable for shredding are used to train the learning model on features for representing normal obsolete scrap. When an image containing objects unsuitable for shredding is input to a trained model generated by learning normal obsolete scrap, the model outputs the abnormal part and the degree of anomaly as an anomaly. When this model is adopted, the probability of an object being unsuitable for shredding output to the operator is based on the degree of anomaly. For example, the degree of anomaly value is normalized to fall within the range of 0.0 to 1.0, and this degree of anomaly is considered the probability of an object being unsuitable for shredding. A learning model using this method outputs whether an object is abnormal, i.e., whether it contains objects unsuitable for shredding, but does not output the type of object, such as "gas cylinder" or "structural steel."

[0043] The learning model is not limited to the one described above. For example, it may be a two-class classification model that classifies captured images into two classes: normal images that do not show objects unsuitable for crushing, and abnormal images that show objects unsuitable for crushing. Alternatively, the learning model may be a multi-class classification model that classifies captured images by type of object unsuitable for crushing. The multi-class classification model differs from the learning models in accordance with the above-mentioned Non-Patent Documents 1 and 2 in that it does not output position information of objects unsuitable for crushing within the captured image.

[0044] In the above explanation, it has been assumed that a single captured image at a certain point in time is input to the learning model, but multiple captured images may also be input in the time direction. For example, an algorithm that also takes into account the time series of captured images, such as a recurrent neural network (RNN), may be used. For example, by adding past judgment results to the current input, it is possible to improve the judgment accuracy of the current captured image to be judged.

[0045] The model generation unit 203 starts the learning model generation process in advance based on instructions from a user before removing the unsuitable materials for shredding as a preliminary step before feeding the materials into a shredder facility using the unsuitable materials for shredding removal system 100. Alternatively, the model generation unit 203 may periodically execute the learning model generation process.

[0046] The learning conditions of the learning model in this embodiment include model conditions, dataset conditions, and learning setting conditions. The model conditions are conditions related to the structure of the neural network. The dataset conditions include conditions for selecting learning data to be input to the neural network during learning, conditions for preprocessing the data, and conditions for image enhancement methods. The learning setting conditions include initialization conditions for neural network parameters such as weights and biases, conditions for optimization methods, and conditions for loss functions. Here, the loss function conditions also include conditions for regularization functions.

[0047] When the learning model generation process starts, first, the model generation unit 203 acquires, from the data storage unit 205, learning data necessary for generating a learning model capable of detecting materials unsuitable for crushing contained in obsolete scrap from images captured by the surveillance camera 5. Then, the model generation unit 203 uses the acquired learning data to generate a learning model capable of detecting materials unsuitable for crushing through machine learning.

[0048] When generating a learning model that learns the characteristics of objects unsuitable for crushing in an image and calculates the type, location, and probability that the object is unsuitable for crushing upon detection, the model generation unit 203 inputs captured images containing objects unsuitable for crushing obtained from the data storage unit 205 into the learning model, and optimizes the learning model so that the location (area) of the object unsuitable for crushing output by the learning model approaches the correct location of the object unsuitable for crushing, and so that the type of object unsuitable for crushing and the probability that the object is unsuitable for crushing are equal to or greater than a predetermined reference value (e.g., 100%). When this type of learning model is used to detect objects unsuitable for crushing, the learning model outputs coordinate data indicating the type of object unsuitable for crushing, the location (area) of the object unsuitable for crushing, and a probability value indicating the degree of certainty (see, for example, Non-Patent Document 1).

[0049] On the other hand, when generating a learning model that uses photographed images of normal obsolete scrap that do not contain objects unsuitable for shredding as training data to learn the overall characteristics of normal obsolete scrap, and that, upon detection, only recognizes the presence of objects unsuitable for shredding in the obsolete scrap and calculates the location and degree of abnormality, the model generation unit 203 inputs photographed images of normal obsolete scrap that do not contain objects unsuitable for shredding acquired from the data storage unit 205 into the learning model to learn the overall characteristics of normal obsolete scrap. The generated learning model is optimized so that it can express (output) that the obsolete scrap does not contain any objects unsuitable for shredding. In this case, when a photographed image containing objects unsuitable for shredding is input to the learning model, the location of the objects unsuitable for shredding and the probability that they are objects unsuitable for shredding are calculated using a difference image or anomaly degree between the photographed image input to the learning model and the photographed image output from the learning model (see, for example, Non-Patent Document 3).

[0050] After generating a learning model through machine learning, the model generation unit 203 outputs the learning model to the model output unit 204.

[0051] The model output unit 204 outputs the learning model generated by the model generation unit 203. For example, the model output unit 204 outputs the learning model generated by the model generation unit 203 to the unsuitable object identification unit 202 so that the unsuitable object identification unit 202 can use the model when identifying the type, location, and probability that an object is unsuitable for crushing.

[0052] Next, a processing procedure for detecting objects unsuitable for crushing using the learning model generated by the above-described procedure will be described. Fig. 4 is a flowchart showing an example of a processing procedure for detecting objects unsuitable for crushing using the learning model by the information processing device 10 in this embodiment. The processing in Fig. 4 is executed by the CPU 301 reading out a control program stored in the ROM 302.

[0053] First, in step S401, the image acquisition unit 201 acquires captured images in real time from the surveillance cameras 5. The acquired images may be moving images or still images. If multiple surveillance cameras 5 are installed, the images are acquired in real time from these surveillance cameras 5.

[0054] Next, in step S402, the unsuitable object identification unit 202 inputs the photographed image acquired by the image acquisition unit 201 into the learning model generated by the model generation unit 203 in the above-mentioned learning model generation process, and identifies the type, position, and probability that the object is an unsuitable object for crushing. If the probability that the object is an unsuitable object for crushing is equal to or greater than a predetermined value, the object is identified as a candidate for an unsuitable object for crushing.

[0055] Next, in step S403, the volume calculation unit 206 inputs the three-dimensional shape measurement results from the three-dimensional shape measurement device 8 and calculates the volume or height of each obsolete scrap from the measurement results. At this time, information on the position and time when the three-dimensional shape was measured is also input so that the captured image can be matched with the capture time. Note that the processing of step S403 may be performed before step S401 or S402.

[0056] Next, in step S404, the determination unit 207 acquires information on the volume or height calculated by the volume calculation unit 206 for the candidate object unsuitable for shredding identified in step S402. Then, taking into consideration the length, width, and height of the candidate object unsuitable for shredding, it determines whether the candidate object unsuitable for shredding identified in step S402 is an object unsuitable for shredding that should be removed.

[0057] Next, in step S405, the result output unit 208 outputs information according to the determination result in step S404. For example, if the object is determined to be unsuitable for shredding to be removed in step S404 and information is to be output to a display device (not shown), the result output unit 208 generates a display screen including an image of the object unsuitable for shredding 701 enclosed in a rectangle 702 in the captured image acquired by the image acquisition unit 201, as shown in FIG. 7A, or a display screen including an image of the object unsuitable for shredding 701 marked with a mark, as shown in FIG. 7B, and notifies the operator by displaying the display screen. At this time, if the type of the object unsuitable for shredding can also be identified, information about the type of the object unsuitable for shredding can also be displayed, allowing the operator to more easily find and remove the object when removing it.

[0058] On the other hand, if it is determined in step S404 that the object is unsuitable for crushing and should be removed, and audio data is to be output to a speaker (not shown), the result output unit 208 generates audio data for notifying the type and location of the object unsuitable for crushing and outputs the audio data to the speaker. Also, if it is not determined in step S404 that the object is unsuitable for crushing and should be removed, nothing may be output, and the captured image acquired by the image acquisition unit 201 may be displayed directly on the display device.

[0059] In step S406, the image acquisition unit 201 determines whether or not to terminate the process of detecting objects unsuitable for shredding. This determination is made, for example, based on whether or not the operator has operated a keyboard or the like to input an instruction to terminate the detection of objects unsuitable for shredding. If the result of this determination is to continue the process, the flow returns to step S401, and the process of detecting objects unsuitable for shredding continues. On the other hand, if the process is to end, the process of FIG. 4 is terminated.

[0060] As described above, according to this embodiment, in the first step, heavy obsolete scrap is discharged by the drum-type magnetic separator 3, which prevents obsolete scrap with few cavities, such as heavy iron blocks, from being input into the shredder facility. On the other hand, although there is a possibility that gas cylinders with large cavities and alloys with low specific gravity will not be discharged by the drum-type magnetic separator 3, these can be subsequently identified using a learning model from images captured by the surveillance camera 5, which more reliably prevents such obsolete scrap from being input into the shredder facility.

[0061] Conventionally, magnetic materials and non-magnetic materials have been separated using drum-type magnetic separators such as those described in Patent Document 3, but the drum-type magnetic separator 3 of this embodiment is different from conventional ones in that it separates heavy waste scrap from light waste scrap among magnetic materials. Note that, although an example in which a learning model is generated in the information processing device 10 has been described in this embodiment, it is also possible to omit the learning function and store a learning model generated by another external device, and perform inference only using the learning model.

[0062] (Second embodiment) In the first embodiment, an example was described in which the drum-type magnetic separator 3 discharges not only non-magnetic objects that cannot be attracted by the magnetic force of an electromagnet, but also magnetic objects unsuitable for crushing, such as thick and heavy objects, out of the system. The drum-type magnetic separator shown in FIG. 5 is a pickup-type drum-type magnetic separator, and in order to successfully drop and discharge large unsuitable objects for crushing, such as thick and heavy objects 6b, out of the system, it is necessary to increase the clearance, which is the distance between the tip of the first vibrating feeder 2 and the rotating drum 33. On the other hand, if the clearance is made too large, thin and lightweight objects 6a cannot be attracted to the rotating drum 33 for crushing.

[0063] Therefore, in the unsuitable shredding material removal system 100 shown in Fig. 1, an overfeed type drum type magnetic separator may be used instead of the pickup type drum type magnetic separator shown in Fig. 5. In the following, in this embodiment, only the points that are different from the first embodiment will be described.

[0064] FIG. 8 is a diagram illustrating an overview of an overfeed-type drum magnetic separator that discharges unsuitable materials to be shredded. As shown in FIG. 8, the drum magnetic separator 80 is similar to the pickup-type drum magnetic separator shown in FIG. 5 in that it rotates a rotating drum 83 equipped with an electromagnet 82 around a drum shaft 81 to attract and collect thin and lightweight crushed materials 6a from waste scrap 6 onto the rotating drum 83. However, in this embodiment, the crushed materials 6a, such as thin and lightweight materials, the large unsuitable materials 6b, such as thick and heavy materials, and the non-magnetic materials 6c transported by the first vibrating feeder 2 are first loaded onto the rotating drum 83. The crushed materials 6a, the unsuitable materials 6b, and the non-magnetic materials 6c are then separated by utilizing the fact that the falling point changes depending on the balance between magnetic force and gravity. Note that, as in the example shown in FIG. 5, the electromagnet 82 does not rotate. As described above, the electromagnet 82 may be configured in any shape and any shape suitable for use in a rotating drum, as long as it can separate the materials to be crushed 6a from the materials not suitable for crushing 6b and the non-magnetic materials 6c. 83 The position at is arbitrary. 82 The crushed materials 6a attracted to the rotating drum 83 by the electromagnet 82 move as the rotating drum 83 rotates, and remain attracted until they reach the magnetic field of the electromagnet 82. When they leave the magnetic field of the electromagnet 82, the crushed materials 6a fall by gravity and are separated from the drum-type magnetic separator 80. On the other hand, among the materials unsuitable for crushing 6b, thick and heavy materials that are equal to or greater than a predetermined weight cannot maintain their attracted state until they leave the magnetic field of the electromagnet 82 as the rotating drum 83 rotates, and will fall when the balance between the magnetic force and gravity is lost along the way.

[0065] In the case of non-magnetic objects 6c, they are not attracted to the rotating drum 83 by the electromagnet 82, and therefore, the non-magnetic objects 6c placed on the rotating drum 83 simply fall by gravity as the rotating drum 83 rotates. Large unsuitable objects 6b are magnetic and are attracted to the rotating drum 83 by the magnetic force of the electromagnet 82. However, as the rotating drum 83 rotates, the force of gravity on the unsuitable objects 6b pulling them away from the rotating drum 83 becomes greater, and the unsuitable objects 6b simply fall. In this embodiment, all transported objects, including thin and lightweight objects 6a to be crushed, unsuitable objects 6b, and non-magnetic objects 6c, are temporarily placed on the rotating drum 83. Therefore, the height of the first vibrating feeder 2 is set to be the same as or slightly lower than the height of the rotating drum 83. However, the first vibrating feeder 2 may be set to be higher than the rotating drum 83 so that waste scrap falls onto the rotating drum 83.

[0066] As described above, in the case of an overfeed type drum type magnetic separator, the tip of the first vibrating feeder 2 and the rotating drum 83 There is almost no need to provide a distance (clearance) between the electromagnet 82 and the drum magnetic separator. Therefore, thin and lightweight materials 6a to be crushed can be properly separated from thick and heavy large materials 6b that are not suitable for crushing simply by adjusting the magnetic force of the electromagnet 82. When a pickup-type drum magnetic separator is used, the clearance must be adjusted each time the size of the typical waste scrap being transported to the drum magnetic separator changes. In contrast, an overfeed-type drum magnetic separator does not require clearance adjustment even when the size of the typical waste scrap varies greatly, making it particularly effective in such cases.

[0067] (Third embodiment) In the first embodiment, when an object unsuitable for shredding is detected by the information processing device 10, the operator checks the screen shown in FIG. 7A or 7B and either directly removes the object unsuitable for shredding or operates a robot arm or the like to remove the object unsuitable for shredding. In this embodiment, an example will be described in which a hanging magnetic separator is provided above the second vibrating feeder 4 and the object unsuitable for shredding detected by the information processing device 10 is removed by magnetic force. Hereinafter, only the differences between this embodiment and the first embodiment will be described.

[0068] 9 is a diagram for explaining an outline of the removal of unsuitable materials for shredding that have been transported onto the second vibrating feeder 4 in this embodiment. As shown in FIG. 9, this embodiment is configured such that a hanging magnetic separator 91 is further provided as a removal device behind the monitoring camera 5 in the unsuitable materials for shredding removal system 100 shown in FIG.

[0069] The hanging-type magnetic separator 91 is installed above the second vibrating feeder 4, and its magnetic force is normally OFF when the information processing device 10 has not detected any unsuitable materials for shredding. The magnetic force of the hanging-type magnetic separator 91 can be switched ON / OFF by a control device (not shown). When the information processing device 10 detects unsuitable materials for shredding, this information is input to the control device, and the magnetic force of the hanging-type magnetic separator 91 is switched ON. Specifically, when the information processing device 10 detects unsuitable materials for shredding, the result output unit 208 notifies the control device that controls the hanging-type magnetic separator 91 that unsuitable materials for shredding are present. At this time, the result output unit 208 also notifies the control device that controls the hanging-type magnetic separator 91 of the timing for turning on the magnetic force, which is set to coincide with the time when the detected unsuitable materials for shredding are within the appropriate range of the magnetic force of the hanging-type magnetic separator 91. For example, the result output unit 208 may also notify the timing for turning on the magnetic force depending on the feed speed of the second vibrating feeder 4 and the distance between the position on the second vibrating feeder 4 photographed by the monitoring camera 5 and the position directly below the hanging magnetic separator 91. In the above, the case where the calculation of the timing for turning on the magnetic force is performed by the result output unit 208 has been described, but the calculation of the timing for turning on the magnetic force may also be performed by a separate device.

[0070] When the control device receives a notification from the information processing device 10 that materials unsuitable for shredding are included, the control device turns on the magnetic force of the hanging-type magnetic separator 91 after a predetermined time, and causes the materials unsuitable for shredding 93 being transported on the second vibrating feeder 4 to be attracted to the hanging-type magnetic separator 91. As the hanging-type magnetic separator 91, for example, a known type such as that described in the microfilm of Japanese Utility Model Application No. 61-110324 (Japanese Utility Model Application Publication No. 63-16850) can be used.

[0071] A conveyor that moves in the direction of box 94 that stores materials unsuitable for shredding (in a direction perpendicular to second vibrating feeder 4) is provided on the underside of hanging magnetic separator 91, and materials unsuitable for shredding 93 move toward directly above box 94 that stores materials unsuitable for shredding while being attracted to the conveyor, and when materials unsuitable for shredding 93 reach a position where they can fall into box 94, such as directly above box 94, the magnetic force of hanging magnetic separator 91 no longer reaches that position, so materials unsuitable for shredding 93 fall into box 94 that stores materials unsuitable for shredding. Then, after all of the materials unsuitable for shredding have fallen, the control device turns the magnetic force of hanging magnetic separator 91 back off. On the other hand, crushed materials 92 to be fed into the shredder facility are not attracted to the hanging magnetic separator 91, but are transported directly to the edge of the second vibrating feeder 4, where they drop and are collected in a box 95 that stores waste scrap. The magnetic force of the hanging magnetic separator 91 is adjusted in advance so that when the magnetic force of the hanging magnetic separator 91 is turned on, it can attract only materials unsuitable for shredding.

[0072] As described above, in this embodiment, even after detecting unsuitable materials for shredding, simply by switching the magnetic force of the hanging magnetic separator 91 on and off, it is possible to separate the waste scrap suitable for shredding from the unsuitable materials. Furthermore, because the magnetic force of the hanging magnetic separator 91 is switched on when unsuitable materials for shredding are detected, the display of the screen shown in FIG. 7A or 7B may be unnecessary. That is, when unsuitable materials for shredding are detected, the output indicating the presence of unsuitable materials for shredding may not be a display device that generates a screen (e.g., FIG. 7A or 7B) intended to prompt the operator to remove the unsuitable materials, but may be a removal device that automatically removes the unsuitable materials. Furthermore, although the above describes an example in which unsuitable materials for shredding 93 are collected in box 94 and other waste scrap are collected in box 95, the reverse may also be true: unsuitable materials for shredding 93 are collected in box 95 and other waste scrap are collected in box 94. In this case, the ON / OFF timing of the hanging magnetic separator is also reversed. That is, it is turned OFF only when materials unsuitable for shredding are detected, and is ON at other times.

[0073] (Fourth embodiment) In the first embodiment, volume or height information for each obsolete scrap was acquired based on the three-dimensional shape measurement results, and whether or not a candidate for unsuitable shredding was unsuitable for shredding and should be removed was determined. However, for obsolete scrap that may cause damage to shredder equipment, strictly speaking, thickness is more important than height. Furthermore, obsolete scrap transported by the second vibrating feeder 4 may be transported in piles. In such cases, the thickness of each pile of obsolete scrap cannot be accurately measured based on the height of the obsolete scrap alone. Therefore, in this embodiment, thickness information for each obsolete scrap is also acquired, enabling more appropriate identification of unsuitable shredding items. Below, only the differences between this embodiment and the first embodiment will be described.

[0074] Furthermore, in step S403, the volume calculation unit 206 calculates the thickness of each obsolete scrap based on the measurement results input from the three-dimensional shape measurement device 8. As in the first embodiment, thickness calculation may be omitted for obsolete scrap that is clearly not unsuitable for crushing based on the three-dimensional shape measurement results. Specific procedures for calculating the thickness of each obsolete scrap are described below.

[0075] FIG. 10A is a diagram showing a specific example of basic shape information. Basic shape information is a two-dimensional image of an object used to obtain three-dimensional shape information. The volume calculation unit 206 acquires, for example, a two-dimensional image of the object as basic shape information, as shown in FIG. 10A. The two-dimensional image of the object is a partial image obtained by filtering a partial area including the object from a captured image acquired by the image acquisition unit 201. Such filtering may be, for example, a process of extracting a fixedly set area (e.g., an area in which the object is always reflected), a process of extracting an area having specific color information (color information possessed by the object), or a process of extracting an area having a specific shape, such as the shape of a typical object unsuitable for crushing.

[0076] Next, the volume calculation unit 206 generates an image of the object showing edges, for example, by performing image processing on the two-dimensional image to extract edges (line segments corresponding to the outline of the object). Fig. 10B is a diagram showing a specific example of an image showing edges extracted from the two-dimensional image of Fig. 10A. Such edge extraction processing may be performed, for example, by applying a high-pass filter to the two-dimensional image.

[0077] Furthermore, the volume calculation unit 206 generates an image showing the surfaces by, for example, performing image processing on the two-dimensional image to extract surfaces. Fig. 10C is a diagram showing a specific example of an image showing the surfaces extracted from the two-dimensional image of Fig. 10A. The processing for extracting such surfaces may be performed, for example, by detecting edges in the two-dimensional image, detecting areas surrounded by the edges, and labeling each detected area (associating each detected area with identification information for each area). Each labeled area may be detected as a single surface.

[0078] In addition, if the measurement results of the three-dimensional shape measuring device 8 include point cloud data that is information representing the shape of each obsolete scrap, the surface of each obsolete scrap may be identified from the point cloud data.

[0079] FIG. 11A is a diagram illustrating a specific example of point cloud data. For example, when point cloud data of an object is obtained from the three-dimensional shape measuring device 8 as shown in FIG. 11A, the volume calculation unit 206 generates information indicating edges by, for example, performing edge extraction processing on the point cloud data. FIG. 11B is a diagram illustrating a specific example of edges extracted from the point cloud data of FIG. 11A. The process of extracting such edges may be performed as follows: First, a normal vector is calculated based on data of a predetermined number of points located nearby in the point cloud data. For example, a normal vector for a plane including three adjacent points may be calculated based on data of the three adjacent points. Adjacent areas whose normal vector directions are within a predetermined threshold are determined to be the same surface, and surfaces are determined for all point cloud data of the object. Line segments indicating boundaries where surfaces meet are extracted as edges. This process is merely an example of a process for acquiring edge information from shape information (e.g., point cloud data). Edge information may also be acquired from point cloud data by other processes.

[0080] Furthermore, the volume calculation unit 206 generates information identifying the surfaces, for example, by performing a process of extracting surfaces from the point cloud data. FIG. 11C is a diagram showing a specific example of surfaces extracted from the point cloud data of FIG. 11A. As described above, the process of extracting such surfaces may involve calculating normal vectors based on data of a predetermined number of points located nearby in the point cloud data, and extracting each surface based on the normal vectors. By performing one or more of the processes described above, the volume calculation unit 206 obtains shape information related to edges and surfaces. Note that the volume calculation unit 206 may obtain shape information by a process different from the process described above.

[0081] The volume calculation unit 206 may perform further processing on the edges or faces extracted by the above-described processing to obtain other shape information as well.

[0082] Once the edge and face information has been acquired as shape information as described above, the volume calculation unit 206 acquires information indicating the length between parallel edges (line segments) for each face, finds the minimum value of the multiple lengths found within each rectangular prism (each individual), and sets this value as the thickness of each waste scrap.

[0083] The above procedure assumes that the obsolete scrap is a rectangular parallelepiped and calculates the thickness of each obsolete scrap. However, obsolete scrap comes in a variety of shapes, including pieces like a partially broken steel pipe. In this case, it is not clear which surface thickness should be considered when determining the potential for damage to shredder equipment. Therefore, after identifying the surfaces as described above, the information can be input into a deep learning model or similar to output the surfaces that should be considered when calculating the thickness of the obsolete scrap. In the example of Figure 12A, the volume calculation unit 206 first identifies surfaces A through E using two-dimensional images or point cloud data. Then, using a deep learning model or similar, it identifies surfaces A, C, and D (the shaded areas on the right side of Figure 12) as surfaces that should be considered. When using a deep learning model, all surfaces identified in the obsolete scrap are input into the deep learning model, and the surfaces that should be considered for the potential for damage to shredder equipment are output as the identified results. Alternatively, as shown in the example of Figure 12B, two-dimensional images or point cloud data may be input and another deep learning model may directly output noteworthy surfaces. When using this deep learning model, two-dimensional images or point cloud data of obsolete scrap are input to the deep learning model, and noteworthy surfaces are output as identified results in consideration of the possibility of causing damage to shredder equipment. Information indicating the length between parallel edges (line segments) of the noteworthy surfaces is then similarly obtained, and the minimum value, for example, is used as the thickness of the obsolete scrap.

[0084] After calculating the thickness of each obsolete scrap as described above, the determination unit 207 determines in step S404 whether the candidate obsolete scrap is an object that should be removed based on the thickness information of each obsolete scrap. For example, if multiple obsolete scraps are determined to be a single object in a pile, the volume or height of the pile will be greater than that of the individual objects, but the thickness will not increase even if the pile is stacked. Thus, according to this embodiment, even when obsolete scrap is transported in a pile on the second vibrating feeder 4, the thickness information of each obsolete scrap can be obtained to more appropriately identify the obsolete scrap.

[0085] Furthermore, when acquiring shape information of obsolete scrap using the point cloud data shown in FIG. 11A, at least one of the volume, height, and thickness of the obsolete scrap can be acquired without using photographic images. Therefore, when determining whether a candidate for obsolete scrap should be removed based solely on the volume, height, or thickness information of each obsolete scrap, the identification of the candidate for obsolete scrap by the unsuitable object identifier 202 may be omitted, and only objects with a volume, height, or thickness equal to or greater than a predetermined value may be identified as unsuitable for shredding. This eliminates the need for a monitoring camera 5, allowing the identification of objects unsuitable for shredding solely from the measurement results of the three-dimensional shape measuring device 8. Alternatively, multiple three-dimensional shape measuring devices may be installed, and the measurement results of these devices may be integrated to more accurately acquire thickness information for the objects unsuitable for shredding.

[0086] (Other embodiments) The information processing device of each of the above-described embodiments is specifically configured as a computer system or device. Therefore, it goes without saying that the functions can also be achieved by supplying a storage medium storing software program code for realizing the above-described functions to the system or device, and having the computer (or CPU or MPU) of the system or device read and execute the program code stored in the storage medium.

[0087] In this case, the program code itself read from the storage medium will realize the functions of the above-mentioned embodiments, and the program code itself and the storage medium storing the program code constitute the present invention. Examples of storage media that can be used to store the program code include flexible disks, hard disks, optical disks, magneto-optical disks, CD-ROMs, CD-Rs, magnetic tapes, non-volatile memory cards, and ROMs.

[0088] The above-described embodiments of the present invention are merely examples of specific embodiments for carrying out the present invention, and the technical scope of the present invention should not be construed as being limited by these. In other words, the present invention can be embodied in various forms without departing from its technical concept or main features.

[0089] Specifically, in the shredded unsuitable material removal system 100 shown in FIG. 1, unsuitable materials are removed via a pre-shredder 1, a first vibrating feeder 2, a drum-type magnetic separator 3, a second vibrating feeder 4, and a monitoring camera 5 (and a three-dimensional shape measuring device 8), but the shredded unsuitable material removal system 100 may omit some of these components. For example, if there is no large obsolete scrap, the pre-shredder 1 may be omitted. Furthermore, in the first embodiment described above, the three-dimensional shape measuring device 8 may also be omitted.

[0090] Furthermore, in the example of FIG. 1, the shredded unsuitable material removal system 100 includes a drum-type magnetic separator 3 and a monitoring camera 5 (and an information processing device 10) to identify and remove unsuitable materials for shredding. However, either one of these components may be omitted. As an example, the shredded unsuitable material removal system 100 may be configured with only the drum-type magnetic separator 3, or may be configured with only the first vibrating feeder 2 and the drum-type magnetic separator 3. In this case, the first vibrating feeder 2 may be replaced with a general non-vibrating belt conveyor, or may be replaced with a combination of the first vibrating feeder 2 and a general non-vibrating belt conveyor. Furthermore, if the drum-type magnetic separator 3 is omitted, the shredded unsuitable material removal system 100 may be configured with only the second vibrating feeder 4 and the monitoring camera 5 (and an information processing device 10). In this case, the second vibrating feeder 4 may be replaced with a general non-vibrating belt conveyor, or may be replaced with a combination of the second vibrating feeder 4 and a general non-vibrating belt conveyor. On the other hand, when both the drum-type magnetic separator 3 and the monitoring camera 5 are provided, the order may be reversed. That is, after identifying and removing objects unsuitable for shredding using the monitoring camera 5 (and the information processing device 10), magnetic objects of a predetermined weight or more that could not be identified as objects unsuitable for shredding may be removed using the drum-type magnetic separator 3. Furthermore, in each of the configurations described above, the monitoring camera 5 may be replaced with a three-dimensional shape measuring device 8, or may be replaced with a combination of the monitoring camera 5 and the three-dimensional shape measuring device 8. Furthermore, two or more of the above-described embodiments may be combined as appropriate, for example, by combining the first, third, and fourth embodiments, or by combining the second to fourth embodiments. [Industrial Applicability]

[0091] According to the present invention, it is possible to accurately remove from each obsolete scrap material unsuitable for shredding that may damage the shredder equipment before the obsolete scrap is fed into the shredder equipment, and this has great industrial value.

Claims

1. A drum-type magnetic separator constituting a system for removing unsuitable materials for shredding, which removes unsuitable materials for shredding that may cause damage to a shredder facility before the scrap is fed into the shredder facility, A drum-type magnetic separator characterized in that the magnetic force is set so as to attract magnetic material of the scrap that is less than a predetermined weight, and the distance between the tip of a vibrating feeder that transports the scrap and the drum-type magnetic separator is adjustable.

2. 2. The drum-type magnetic separator according to claim 1, wherein at least one of the magnetic force of the magnets and the rotation speed of the drum of the drum-type magnetic separator is further adjustable.

3. A drum-type magnetic separator as described in claim 1, further characterized in that it is configured so that the conveying speed of the vibrating feeder can be adjusted.

4. A drum-type magnetic separator constituting a system for removing unsuitable materials for shredding, which removes unsuitable materials for shredding that may cause damage to a shredder facility before the scrap is fed into the shredder facility, The distance between the tip of the vibrating feeder that transports the scrap and the drum-type magnetic separator is adjustable, the magnetic force of the magnet of the drum-type magnetic separator is set so that magnetic materials of a predetermined weight or more among the scrap fall so as to pass through a gap between the drum-type magnetic separator and the vibrating feeder, and magnetic materials of a weight less than the predetermined weight are attracted to and adsorbed onto the rotating drum so as not to fall into the gap; A drum-type magnetic separator characterized in that the magnetic objects attracted by the magnetic force of the magnet are separated from the rotating drum by being moved out of the magnetic force area of ​​the magnet as the rotating drum rotates.

5. A drum-type magnetic separator constituting a system for removing unsuitable materials for shredding, which removes unsuitable materials for shredding that may cause damage to a shredder facility before the scrap is fed into the shredder facility, The height of the vibration feeder that conveys the scrap is at the same level as or lower than the height of the rotary drum, a magnetic force of the magnet of the drum-type magnetic separator is set so that magnetic materials of less than a predetermined weight among the scrap are attracted to the rotating drum; magnetic materials attracted from the vibrating feeder by the magnetic force of the magnet move out of the magnetic field of the magnet as the rotating drum rotates, thereby separating the attracted magnetic materials from the rotating drum; and magnetic materials of the predetermined weight or more are placed from the vibrating feeder onto the rotating drum, and the magnetic materials of the predetermined weight or more are allowed to fall by gravity before they move out of the magnetic field of the magnet as the rotating drum rotates.

6. 6. The drum-type magnetic separator according to claim 1, wherein the scrap includes scrap roughly crushed by a pre-shredder.

7. A system for removing materials unsuitable for shredding that removes materials unsuitable for shredding that may cause damage to shredder equipment before the scrap is fed into the shredder equipment, an information processing device including: an identifying means for identifying magnetic objects that are unsuitable for shredding based on at least one of a photographed image of the magnetic objects in the scrap and a measurement result of the three-dimensional shape of the magnetic objects; and an output means for outputting a message indicating that the magnetic objects are included in the scrap when the identifying means identifies the magnetic objects as unsuitable for shredding; a drum-type magnetic separator having a magnetic force set to attract magnetic materials of less than a predetermined weight from the scrap excluding the materials unsuitable for shredding identified by the identifying means; A crushing and unsuitable material removal system comprising:

8. A method for separating materials unsuitable for shredding using a drum-type magnetic separator that constitutes an unsuitable material removal system for removing materials unsuitable for shredding that may cause damage to a shredder facility before the scrap is fed into the shredder facility, A method for separating materials unsuitable for shredding, comprising a step of adjusting the distance between the tip of a vibrating feeder that transports the scrap and the rotating drum of the drum-type magnetic separator so as to attract and separate magnetic materials of less than a predetermined weight from the scrap.

9. A method for separating materials unsuitable for shredding in a material unsuitable for shredding removal system, which removes materials unsuitable for shredding that may cause damage to shredder equipment before the scrap is fed into the shredder equipment, comprising: a first step of identifying the magnetic objects unsuitable for shredding based on at least one of photographed images and three-dimensional shape measurement results of the magnetic objects in the scrap, and thereby removing the magnetic objects unsuitable for shredding; a second step of attracting and separating magnetic materials of less than a predetermined weight from the scrap excluding the materials unsuitable for shredding identified in the first step using a drum-type magnetic separator; A method for separating materials unsuitable for crushing, comprising:

Images