JP2023017263A - Sorting equipment of waste plastics and sorting method of waste plastics - Google Patents

Abstract

To provide sorting equipment which sorts waste plastics by material with high accuracy.SOLUTION: Sorting equipment of waste plastics includes: a surface treatment part which treats surfaces of a waste plastic pieces including black waste plastic pieces; an irradiation part which irradiates the surface-treated waste plastic pieces with light; a reflection spectrum detection part which receives reflected light of the irradiated light and detects a spectrum of the reflected light; a determination part which determines the material of the waste plastic pieces on the basis of the spectrum of the reflected light; and a sorting part which sorts at least the black waste plastic pieces by material on the basis of the result of determination.SELECTED DRAWING: Figure 1

Description

The present disclosure relates to a waste plastic sorting apparatus and a waste plastic sorting method.

BACKGROUND ART Material recycling, in which new materials and products are manufactured using waste plastics, is known as a main method for reusing waste plastics derived from waste home electric appliances, discarded automobiles, and the like. Since collected waste plastics usually contain various kinds (materials) of plastics, in material recycling, it is necessary to sort the waste plastics according to the material according to the recycled product to be manufactured.

As a means for sorting waste plastics, for example, it is known to irradiate a piece of waste plastic with light such as infrared light and use the spectrum of the reflected light obtained by the irradiation to determine the material of the plastic. (For example, Patent Document 1).

JP 2018-100903 A

In order to manufacture high-quality products in material recycling, waste plastics must be sorted with high precision. However, in the conventional sorting of waste plastics using the reflection of light such as infrared rays, halation occurs depending on the intensity of the irradiated light, the irradiation distance, etc., and the reflection spectrum is effective for judging the material. In some cases, it was not possible to obtain enough reflected light to generate Therefore, there is a demand for improved sorting accuracy in a waste plastic sorting apparatus or sorting method that utilizes reflection of light.

Accordingly, one aspect of the present invention aims to provide a sorting apparatus that sorts waste plastics by material with high accuracy.

A waste plastic sorting apparatus according to an aspect of the present invention comprises a surface treatment unit for treating surfaces of waste plastic pieces including black waste plastic pieces, an irradiation unit for irradiating the surface-treated waste plastic pieces with light, and a reflection spectrum detection unit that receives reflected light of the light irradiated by the irradiation unit and detects the spectrum of the reflected light; a determination unit that determines the material of the waste plastic piece based on the spectrum of the reflected light; a sorting unit that sorts at least the black waste plastic pieces according to the material based on the determination result;

According to the present disclosure, it is possible to provide a sorting device capable of sorting waste plastics by material with high accuracy.

1 is a perspective view showing a schematic configuration of a waste plastic sorting apparatus according to an embodiment; Side view of the waste plastic sorting device shown in FIG. A plan view of the waste plastic sorting device shown in FIG. Schematic diagram showing an example of a surface treatment part Functional block diagram of the sorting device Flowchart of waste plastic material discrimination processing according to the embodiment Diagram showing the method of extracting spectra for correction A diagram showing an example of processing for extracting a characteristic wavelength region from a reflected wave spectrum. Diagram showing an example of feature data extraction Diagram showing an example of material discrimination using a decision tree A plan view showing the first material sorting method by the sorting device of the present embodiment. Plan view showing a second material sorting method by the sorting device of the present embodiment A plan view showing a third material sorting method by the sorting device of the present embodiment A plan view showing a fourth material sorting method by the sorting device of the present embodiment Plan view showing the fifth material selection method by the sorting device of the present embodiment A diagram showing an example of the operation screen of the sorting device

Embodiments will be described below with reference to the accompanying drawings. In order to facilitate understanding of the description, the same constituent elements in each drawing are denoted by the same reference numerals as much as possible, and overlapping descriptions are omitted.

In the following description, x-direction, y-direction, and z-direction are directions perpendicular to each other. The x and y directions are horizontal and the z direction is vertical. The x direction is the transport direction of the transport path 3 of the conveyor 2 . The y direction is the width direction of the transport path 3 of the conveyor 2 . In the following, for convenience of explanation, the z positive direction side may be expressed as the upper side, and the z negative direction side may be expressed as the lower side. Also, the negative x direction side may be expressed as upstream, and the positive x direction side may be expressed as downstream.

A schematic configuration of a waste plastic sorting apparatus 1 according to an embodiment of the present invention will be described with reference to FIGS. 1 to 3. FIG. FIG. 1 is a perspective view showing a schematic configuration of a waste plastic sorting apparatus 1 according to this embodiment. FIG. 2 is a side view of the waste plastic sorting apparatus 1 shown in FIG. FIG. 3 is a plan view of the waste plastic sorting apparatus 1 shown in FIG. As shown in FIGS. 1 to 3, the waste plastic sorting device 1 includes a surface treatment section 20 upstream of the device.

The waste plastic sorted by the sorting apparatus 1 according to the present embodiment is an aggregate (waste plastic fragment group) formed by pulverization obtained from scrap home electric appliances, discarded automobiles, and the like. One waste plastic piece may have a plate-like or layered shape, and may have an average maximum length of 5 to 50 mm and an average area of 20 to 2500 mm ² in plan view. In the present embodiment, waste plastic pieces of a predetermined material are extracted from an aggregate of waste plastic pieces including black waste plastic pieces (waste plastic piece group), preferably from an aggregate of black waste plastic pieces (black waste plastic piece group). is to be selected. Further, in the waste plastic pieces sorted out according to the present embodiment, in addition to the black waste plastic pieces, colored waste plastic pieces of other colors such as blue and red may be mixed.

In this specification, black refers to a color with a brightness of 6 or less expressed in Munsell symbols according to JIS8721. The black color of the black waste plastic pieces is usually derived from carbon black (carbon filler) contained in the black waste plastic pieces.

1 to 3, as an example, from a group of waste plastic pieces S1 made of one kind of material and waste plastic pieces S2 made of a different kind of material from the waste plastic pieces, one 1 shows an apparatus for judging and sorting waste plastic pieces of material. In the following, the waste plastic pieces S1 and S2 may be collectively represented by symbol S. The number of materials (kinds) of waste plastic pieces sorted out from the waste plastic piece group is not particularly limited, and may be 2 to 10 kinds. Specific examples of plastic materials include polyethylene (PE), polypropylene (PP), polycarbonate/acrylonitrile-butadiene-styrene (PCABS), acrylonitrile-butadiene-styrene (ABS), polystyrene (PS), polyphenylene ether/polystyrene (PPPEPS). ), polyamide (PA), polycarbonate (PC), polyacetal (POM), polyethylene terephthalate (PET), polyvinyl chloride (PVC), polymethyl methacrylate (PMMA), and the like.

In the waste plastic sorting apparatus 1 according to the present embodiment, the material of the waste plastic is determined based on the reflection spectrum detected from the reflected light obtained by irradiating light such as infrared rays, and the material is determined. later). Here, in the conventional configuration, when light is applied, strong regular reflection (specular reflection) occurs depending on the intensity of the irradiated light, the irradiation distance, etc., and the reflected light (specular reflection) that is effective for determining the material diffuse reflected light) may not be sufficiently obtained. On the other hand, the sorting apparatus 1 according to this embodiment has a surface treatment unit 20, and the surface treatment unit 20 treats the surface of the waste plastic pieces so that appropriate reflected light can be obtained. .

In particular, black plastic has a lower level (strength) of absorption regions inherent to the material than plastics of other colors, and is therefore more affected by surface conditions. In particular, when the glossiness of the plastic surface is relatively high, the influence of the reflection of infrared rays on the plastic surface, especially the influence of specular reflection (specular reflection), becomes large, so the absorption level becomes invisible and it is difficult to distinguish the material. becomes. Therefore, by roughening the surface to a predetermined rough surface state by applying surface treatment, the influence of specular reflection of infrared rays on the plastic surface can be suppressed, and the spectral intensity in the reflected light spectrum can be increased. Differences in intensity can be properly observed. As a result, it is possible to improve the sorting accuracy of the black plastic pieces.

The surface treatment performed by the surface treatment unit 20 may be a treatment that, when irradiated with light, provides a surface state that enables acquisition of a reflection spectrum that is effective in discriminating the material. For example, the surface treatment according to the present embodiment is such that the surface of the waste plastic piece has a glossiness (specular glossiness) (Gs60 (%)) at an incident angle of 60° measured in accordance with JIS Z 8741 of 10 or less. It may be a process to change the surface state as follows. The glossiness at an incident angle of 60° may be preferably 8 or less, more preferably 6 or less, and even more preferably 1.5 or less. Further, the glossiness at the incident angle of 60° may be 0.1 or more. Furthermore, the surface treatment according to the present embodiment changes the surface condition so that the glossiness (specular glossiness) (Gs75 (%)) at an incident angle of 75° measured in accordance with JIS Z 8741 is 25 or less. It may be processing. The glossiness at an incident angle of 75° may be preferably 15 or less, more preferably 10 or less, even more preferably 5 or less. Further, the glossiness at the incident angle of 75° may be 0.1 or more. Further, the surface treatment in the present embodiment is preferably performed so that the glossiness at an incident angle of 60° falls within the above range and the glossiness at an incident angle of 75° falls within the above range. By having the above-mentioned glossiness, particularly glossiness at an incident angle of 60° and/or incident angle of 75°, it is possible to impart an appropriate rough surface condition to the surface of the plastic, thereby turning the waste plastic pieces into black plastic pieces. Even if there is, the sorting accuracy can be increased.

In addition, the surface treatment according to the present embodiment may be a treatment for changing the surface state of the surface of the waste plastic pieces so that the surface roughness average deviation (SMD) is 1 μm or more. The average deviation of surface roughness may be preferably 1.1 μm or more, more preferably 1.2 μm or more. Also, the average deviation of the surface roughness can be preferably 6 m or less, preferably 3 μm or less, more preferably 2.5 μm or less. By performing the surface treatment so that the surface roughness average deviation (SMD) is within the above range, the surface of the plastic can be provided with an appropriate rough surface state. Therefore, even when the waste plastic pieces are black plastic pieces, a proper reflection spectrum can be obtained, and the sorting accuracy can be improved.

In addition, 50% or more, preferably 80% or more of the total surface area of the waste plastic pieces has a glossiness of 10 or less at an incident angle of 60° (specular glossiness (%)) measured in accordance with JIS Z 8741. Satisfy one or more of the conditions that the glossiness (specular glossiness (%)) at an incident angle of 75° measured in accordance with Z 8741 is 25 or less and the surface roughness mean deviation (SMD) is 1 μm or more. In such a state, it is possible to improve the sorting accuracy of waste plastic pieces using infrared rays.

The surface treatment in this embodiment may be a roughening treatment or a smoothing treatment depending on the surface condition of the original waste plastic pieces. Moreover, the surface treatment may be a wet treatment using a liquid, or a dry treatment using no liquid. Specific examples of surface treatment include polishing (or grinding) using abrasive tools and/or abrasives such as wire brushes and sandpaper, and surface treatment using chemicals. Of these, the polishing treatment is preferred because it produces relatively little waste and the like and is easy to dispose of.

FIG. 4 is a schematic diagram of an example of the surface treatment section 20. As shown in FIG. The surface treatment section 20 shown in FIG. 4 includes a plurality of rollers having rough surfaces. Then, by passing the waste plastic piece S′ before the surface treatment between a plurality of rollers, the surface of the waste plastic piece S′ is scraped to form fine irregularities and/or excessively large irregularities. By eliminating the unevenness, a waste plastic piece S having unevenness of an appropriate size is obtained. The surface of the waste plastic piece on which unevenness of an appropriate size is formed has the above-mentioned predetermined glossiness, and the sorting device 1 can determine the type of plastic using light irradiation with higher accuracy. can be done.

The surface treatment unit 20 shown in FIG. 4 includes a large roller 21 that rotates in the direction in which waste plastic pieces are conveyed, and small-diameter rough surface rollers 23 that face the large roller 21 and rotate in the direction opposite to the large roller 21. , 23 are arranged. Rough rollers 23, 23, 23 have brushes or sandpaper attached to their surfaces. Then, the waste plastic pieces S′ before surface treatment supplied from the supply unit 28 are supplied between the large roller 21 and the rough surface rollers 23 , 23 , 23 , conveyed in the conveying direction, and The surface facing the rollers 23, 23, 23 is roughened. In the surface treatment section 20, downstream of the large roller 21 and the rough surface rollers 23, 23, 23, another large roller 22 that rotates in the conveying direction of the waste plastic pieces Small-diameter rough surface rollers 25, 25, 25 rotating at high speed in the opposite direction to 22 are arranged. Like the rough rollers 23, 23, 23, the rough rollers 25, 25, 25 are provided with brushes or sandpaper. The large roller 22 and the rough surface rollers 25, 25, 25 are arranged so that the surface of the waste plastic piece S' opposite to the surface roughened by the rough surface rollers 23, 23, 23 is roughened. With such a configuration, both surfaces of the waste plastic pieces S' have appropriate surface conditions according to the determination of the material in the sorting apparatus 1, and sorting by material can be performed with high accuracy. The number of rotations of the rough surface rollers 23, 23, 23 and the rough surface rollers 25, 25, 25 can be set according to the desired surface condition of the waste plastic pieces. Appropriate surface conditions include a glossiness (specular glossiness (%)) of 10 or less at an incident angle of 60° measured in accordance with JIS Z 8741, and an incident angle of 75 measured in accordance with JIS Z 8741. degree glossiness (specular glossiness (%)) of 25 or less and surface roughness mean deviation (SMD) of 1 μm or more. In the case of waste plastic pieces containing black plastic pieces or consisting of black plastic pieces, the sorting accuracy can be improved by providing the surface condition described above.

The waste plastic piece is a piece of plastic that has been taken out of a waste home appliance, a waste automobile, or the like, and crushed to reduce its size so that it can be easily reused. The surface treatment in this embodiment may be incorporated into the crushing step.

Referring again to FIGS. 1 to 3, processing of waste plastic pieces S after surface treatment in the sorting apparatus 1 will be described. A vibration feeder 8 as an example of a supply unit that sequentially supplies the surface-treated waste plastic pieces S1 and S2 obtained from the surface treatment unit 20, and a transport that transports the waste plastic pieces S1 and S2 supplied by the vibration feeder 8. A conveyor 2 as an example of a section is provided as a main section. The vibrating feeder 8 is supplied with crushed (surface-treated) waste plastic pieces S1 and S2 via, for example, an input hopper. The vibrating feeder 8 supplies the waste plastic pieces S1 and S2 to the conveyor 2 while preventing the waste plastic pieces S1 and S2 from overlapping each other by vibrating the mounting surface on which the waste plastic pieces S1 and S2 are mounted. The conveyor 2 has a conveying path 3 on its upper surface, and conveys the waste plastic pieces S1 and S2 on the conveying path 3 in a direction away from the vibrating feeder 8. As shown in FIG.

The sorting apparatus 1 also includes a lighting unit 10 as an example of an irradiation unit that irradiates the waste plastic pieces S1 and S2 with infrared rays, and a medium light as an example of a reflection spectrum detection unit that detects reflection spectra from the waste plastic pieces S1 and S2. An infrared camera 4 and a determination device 5 for determining or identifying the material of the waste plastic pieces S1 and S2 based on the reflection spectrum detected by the mid-infrared camera 4 are provided.

The illumination 10 has a lamp 10A (see FIG. 7), which is an infrared light source such as a halogen tungsten lamp, and irradiates (emits) infrared rays from the lamp 10A toward the waste plastic pieces S1 and S2. In addition, the illumination 10 is installed so that the reflected light from the waste plastic pieces S1 and S2 enters the mid-infrared camera 4. is installed in

The irradiation light applied to the waste plastic pieces may include infrared rays of 2 to 8 μm, preferably mid-infrared rays of more than 3 μm, more specifically infrared rays of more than 3 μm and 8 μm or less. Since the mid-infrared rays in the above wavelength range include a region where the light absorption rate of black plastic is relatively low, even for black waste plastic, the reflected light spectrum is effective for judging the material of the plastic (significant depending on the material). A reflected light spectrum) can be obtained in which differences can be observed.

For example, as shown in FIG. 1, a single mid-infrared camera 4 can measure the entire area of the conveyor 2 in the width direction (y direction). can receive the reflected near-infrared light from the black waste plastic pieces S1 and S2 and measure the spectrum of the reflected light for each region. The mid-infrared camera 4 may be composed of, for example, a camera with a spectroscope for an infrared wavelength range of 3 μm or more or more than 3 μm. The mid-infrared camera 4 performs measurement at a scanning frequency of 230 Hz, for example, and transmits 318 spectrum data to the discriminating device 5 for each scan. Based on the 318 spectrum data received from the mid-infrared camera 4, the discriminating device 5 outputs the result of material discrimination of each of the 318 regions to the injection control section 6, which will be described later.

The reflected light received by the mid-infrared camera 4 may preferably contain infrared light in the wavelength region of more than 3 μm, more preferably more than 3 μm and less than or equal to 8 μm, and even more preferably more than 3 μm and less than or equal to 5 μm. By receiving the reflected light in the above wavelength range, it is possible to obtain effective data for determining the material quality of the black waste plastic. That is, in the spectral intensity of the reflected light within the above wavelength range, a significant difference can be observed depending on the material.

Further, the sorting device 1 includes a jet nozzle array 7 that jets air laterally or obliquely in a direction intersecting the conveying direction on the downstream side of the conveying direction (x direction) of the conveyor 2 . The injection nozzle row 7 is formed by arranging a plurality of (for example, 318) injection nozzles side by side in the width direction (y direction) of the conveyor 2, and the operation of each injection nozzle is controlled by the injection control unit 6. The injection control unit 6 can cause or not to inject air from the injection nozzles of the injection nozzle row 7 according to the material determination result received from the discrimination device 5 . That is, it is possible to select target waste plastic pieces and blow air thereon (selective blowing). Then, the black waste plastic pieces S1 and S2 are sorted and dropped into a plurality of areas (for example, collection hoppers or containers) separated by, for example, a partition plate 9 (FIG. 2), and waste plastics of desired materials are sorted and collected. . That is, in this embodiment, the injection control unit 6 and the injection nozzle array 7 collect pieces of a desired material from the waste plastic pieces flowing on the conveying path 3 of the conveyor 2 based on the material determination result by the discriminating device 5. It functions as the sorting unit 12 .

In the examples shown in FIGS. 1 to 3, the sorting unit 12 sorts the waste plastic pieces S on the conveyer 2 by selective blowing, which is to blow off or not blow off, by using the injection of air or a predetermined gas. , the form of sorting is not limited to the illustrated one. For example, the information on the material determination result by the discriminating device 5 may be transmitted to the robot arm, and the robot arm may sort the waste plastic pieces according to the material to separate the waste plastic pieces.

The operation of the sorting apparatus 1, that is, the treatment of the waste plastic pieces supplied from the surface treatment section 20 will be described. For example, when the crushed waste plastic pieces S1 and S2 are supplied to the vibrating feeder 8 via an input hopper or the like, the vibrating feeder 8 vibrates the supplied waste plastic pieces S1 and S2 so that they do not overlap each other. and conveyed downstream and supplied to the conveyor 2.

The waste plastic pieces S1 and S2 supplied to the conveying path 3 on the upper surface of the conveyor 2 are conveyed in the conveying direction on the positive x side, and captured by the mid-infrared camera 4. is irradiated. The mid-infrared camera 4 receives infrared light reflected by the waste plastic pieces S 1 and S 2 emitted from the illumination 10 and outputs the light reception result (light reception spectrum data) to the discriminating device 5 .

The discriminating device 5 identifies the material of the waste plastic pieces S1 and S2 based on the light receiving result input from the mid-infrared camera 4. FIG. The details of the material determination method by the determination device 5 will be described later with reference to FIGS. 5 to 10. FIG. The discrimination device 5 outputs the material identification result to the injection control section 6 .

The injection control unit 6 selects an injection nozzle corresponding to the material from among the plurality of injection nozzles included in the injection nozzle row 7 and transmits a control signal at the appropriate timing. Each injection nozzle of the injection nozzle row 7 that has received the control signal opens the nozzle port and injects air. By injecting air from the injection nozzle at an appropriate timing according to the discrimination result of the discriminating device 5, it is possible to separate and collect the materials to be sorted and the materials not to be sorted.

In the example shown in FIGS. 1 to 3, the waste plastic pieces S1 on the conveyor 2 are blown away by air from the air injection nozzle that receives the control signal, fall, and are collected in a collection container or the like. In addition, since the black waste plastic pieces S2 on the conveyor 2 do not receive air from the injection nozzle, they are collected in a collection container or the like different from the black waste plastic pieces S1. In this way, by individually injecting and stopping the plurality of injection nozzles included in the injection nozzle row 7, it is possible to sort and collect waste plastic pieces of a predetermined material from a group of waste plastic pieces of a plurality of materials.

According to this embodiment, the waste plastic pieces to be sorted are surface-treated and have a predetermined surface roughness, preferably on both sides. can have Therefore, in the sorting section 12, the targeted waste plastic pieces are surely blown away, and the non-targeted waste plastic pieces are surely not blown away, which also contributes to the improvement of the sorting accuracy.

Next, with reference to FIGS. 5 to 10, the material judgment and discrimination of the waste plastic by the discrimination device 5 will be described. FIG. 5 is a functional block diagram of the discrimination device 5. As shown in FIG.

As shown in FIG. 5, the discriminating device 5 has a preprocessing section 51, and further has a first determining section 52, a second determining section 53, and a third determining section 54 (collectively referred to as determining section).

The preprocessing unit 51 performs preprocessing such as correction and processing of the reflection spectra of the black waste plastic pieces S1 and S2 detected by the mid-infrared camera 4 . The preprocessing unit 51 corrects the detected reflection spectrum using, for example, the spectrum measured under bright reflected light conditions and the spectrum measured under dark reflected light conditions. "Dark condition (dark condition)" means a condition that is relatively darker than the "bright condition (bright condition)" described above. Further, the preprocessing unit 51 performs processing to cut out a predetermined frequency range from the corrected reflection spectrum.

The first determination unit 52 determines whether the spectra detected by the mid-infrared camera 4 belong to the waste plastic pieces S1, S2 or the conveying path 3 of the conveyor 2. FIG. The first determination unit 52 performs determination using a learned One Class SVM (Support Vector Machine).

One Class SVM is a type of SVM, which is a type of machine learning classification algorithm. In SVM, the support vector of each class (located closest to other classes in the learning data) is used as a reference, and a discrimination boundary is set so that the Euclidean distance between them is maximized. Also, if the features are non-linear, a kernel is used to map the data to the feature space. By appropriately selecting the kernel, it is possible to draw a discriminative boundary even for complicated data arrangements.

One Class SVM uses a technique called a kernel trick for one type of learning data to map the data to a high-dimensional feature space. At this time, since the learning data are mapped so as to be located far from the origin, data that are not similar to the original learning data gather near the origin. This property is used to distinguish between normal data (conveyor 2) and abnormal data (objects (waste plastic pieces S1, S2)).

By using the One Class SVM with excellent pattern discrimination ability in the first determination unit 52, it is possible to determine with high accuracy whether the reflection spectrum is reflected by the waste plastic pieces S1 and S2 or the conveying path 3 of the conveyor 2. can be identified. It should be noted that a classification method of supervised learning of machine learning other than One Class SVM may be applied to the first determination unit 52 .

The second determination unit 53 extracts feature data Score1 and Score2 (feature amounts) from the spectrum determined as the waste plastic piece by the first determination unit 52 . The feature amount may be, for example, the maximum value, average value, integral value, etc. of the spectral intensity in a predetermined wavelength region, but it is preferable to extract using learned PLS (Partial Least Squares). desirable.

PLS is a kind of supervised learning regression algorithm of machine learning, and performs regression analysis between only a small number of principal components among the principal components calculated from the explanatory variables and the objective variable. In PLS, the principal components are calculated so as to have a large covariance with the objective variable. In this embodiment, PLS is used to calculate two types of feature data Score1 and Score2 based on the explanatory variables of the reflection spectra determined to be reflected by the waste plastic pieces S1 and S2.

By using PLS in the second determination unit 53, it is possible to reduce the multidimensional explanatory variables of the reflection spectrum to a small number of feature amounts, so that it is possible to extract appropriate feature data Score1 and Score2 that are easier to distinguish. . Note that a machine learning multivariate analysis method other than PLS may be applied to the second determination unit 53 .

The third determination unit 54 determines the materials of the waste plastic pieces S1 and S2 corresponding to the two characteristic amounts Score1 and Score2 of the reflection spectrum extracted by the second determination unit 53 . The third determination unit 54 makes a determination using a learned decision tree. Decision trees are a class of supervised learning classification algorithms. A decision tree is a tree structure representing rules for classifying objective variables, and is frequently used in classification problems.

By using a decision tree for the third determination unit 54, the materials of the waste plastic pieces S1 and S2 can be accurately determined from the two feature values Score1 and Score2 of the reflection spectrum. Note that a supervised learning classification method of machine learning other than the decision tree may be applied to the third determination unit 54 .

The discriminating device 5 is physically configured as a computer system including a CPU (Central Processing Unit), RAM (Random Access Memory) and ROM (Read Only Memory) which are main storage devices, a communication module, an auxiliary storage device, and the like. can do. Each function of the discriminating device 5 shown in FIG. This is achieved by reading and writing data in the . That is, by executing the material determination program according to the present embodiment on a computer, the determination device 5 performs function as

The material determination program of this embodiment is stored, for example, in a storage device included in a computer. Part or all of the material determination program may be transmitted via a transmission medium such as a communication line, received by a communication module or the like provided in the computer, and recorded (including installation). In addition, the material identification program is partly or wholly stored in a portable storage medium such as CD-ROM, DVD-ROM, flash memory, etc., and is recorded (including installation) in the computer. may be

The discrimination device 5 may be a circuit composed of an analog circuit, a digital circuit, or a mixed analog/digital circuit. Further, a control circuit for controlling each function of the discriminating device 5 may be provided. Each circuit may be implemented by ASIC (Application Specific Integrated Circuit), FPGA (Field Programmable Gate Array), or the like.

Similarly, the injection control unit 6 can also physically be configured as a computer system including a CPU, RAM and ROM, a communication module, an auxiliary storage device, and the like. The function is realized by loading it.

FIG. 6 is a flowchart of waste plastic material discrimination processing according to the embodiment. Each process of the flowchart shown in FIG. 6 is executed by the discriminating device 5 .

In step S<b>01 , the spectrum S _org (n, w) obtained by the mid-infrared camera 4 is acquired by the preprocessing unit 51 . Here, n is the number of sensors (the number of spectral detection areas divided in the width direction of the conveyor 2 by the mid-infrared camera 4), and when the number of sensors is 318, 0 to 317 corresponding to each detection area. Integers are used. w is the wavelength of the spectrum, and in this embodiment, a total of 131 wavelengths are set in increments of 20 (nm) between 2700 (nm) and 5300 (nm), and an integer from 0 to 130 corresponding to each wavelength is used. That is, S _org (n, w) represents the numerical value of the spectral intensity of the wavelength w in the n-th spectrum detection area along the width direction of the conveyor 2 .

In step S02, the preprocessing unit 51 corrects the spectrum S _org (n, w) acquired in step S01 to calculate the corrected spectrum S _cor (n, w). With this correction, the spectrum due to the influence of changes in the concentration of water vapor and carbon dioxide in the measurement space, the temperature of the black waste plastic pieces S1 and S2 to be measured, the aging deterioration of the illumination 10 and the mid-infrared camera 4, the position on the conveyor 2, etc. Ability to absorb differences in strength characteristics. The corrected spectrum S _cor (n, w) can be calculated, for example, by the following formula (1).

上式中、W_ref（ｎ，ｗ）は、反射光が明るい条件で計測した第１の補正用スペクトルである。D_ref（ｎ，ｗ）は、反射光が上記の明るい条件よりも暗い条件で計測した第２の補正用スペクトルである。これらの補正用スペクトルW_ref（ｎ，ｗ）、D_ref（ｎ，ｗ）は、例えば、材質判別処理を実行する前に中赤外線カメラ４の校正を行うときに抽出できる。

In the above formula, W _ref (n, w) is the first correction spectrum measured under bright reflected light conditions. D _ref (n, w) is the second correction spectrum measured under the condition that the reflected light is darker than the bright condition. These correction spectra W _ref (n, w) and D _ref (n, w) can be extracted, for example, when calibrating the mid-infrared camera 4 before executing the material discrimination process.

FIG. 7 is a diagram showing a method of extracting spectra W _ref (n, w) and D _ref (n, w) for correction. As shown in FIG. 7, a calibration plate 11 for acquiring a correction spectrum is installed in the imaging area of the mid-infrared camera 4 on the conveying path 3 of the conveyor 2, and the spectrum of the reflected light by the mid-infrared camera 4 is By detecting , correction spectra W _ref (n, w) and D _ref (n, w) can be obtained.

In the case of the first correction spectrum W _ref (n, w) measured under bright reflected light conditions, a calibration plate 11 (aluminum, stainless steel, etc.) that reflects all wavelengths in the mid-infrared region was placed, and the illumination 10 was turned on. , data for all wavelengths (w=0 (2700), 2 (2720), . get.

In the case of the second correction spectrum D _ref (n, w) measured under dark reflected light conditions, a calibration plate 11 (aluminum, stainless steel, etc.) that reflects all wavelengths in the mid-infrared region was placed, and the illumination 10 was turned off. (or camera shutter closed), for all sensors (n=0, 1, 2, . , 130 (5300)).

The calibration plate 11 is arranged on the conveying path of the conveyor 2 when acquiring the correction spectra W _ref (n, w) and D _ref (n, w), as indicated by dotted arrows in FIG. 7, for example. 3 and a standby position outside the imaging area of the mid-infrared camera 4 and the irradiation range of the illumination 10. In other words, the calibration plate 11 can be fixed at a predetermined position within the field of view of the mid-infrared camera 4 and at a predetermined position outside the field of view, and preferably movable between both predetermined positions. The calibration plate 11 is preferably processed so that the main surface that receives the light from the illumination 10 has a large surface roughness. This can suppress the occurrence of halation of reflected light on the calibration plate 11 .

Further, the conveyor 2 may be stopped when acquiring the correction spectrum. In this case, if the calibration plate 11 is not positioned correctly in the imaging area of the mid-infrared camera 4 due to some malfunction in the operation of the calibration plate 11, the infrared rays of the illumination 10 irradiate the infrared rays on the conveying path 3 of the conveyor 2. The temperature of the part rises, and there is a risk of burnout or ignition. Therefore, when the calibration plate 11 is not fixed within the field of view of the mid-infrared camera 4, it is preferable to provide an interlock so that the illumination 10 does not emit infrared rays.

As shown in FIG. 7, the illumination 10 has a lamp 10A (sheath heater, carbon lamp, kanthal lamp, etc.) as an infrared light source and a reflector 10B that collects the heat of the lamp 10A. The lamp 10A is formed to extend along the width direction (y direction) of the conveyor 2 and arranged to emit infrared rays in all directions around the axis along the y axis. The reflecting plate 10B is arranged on the opposite side of the conveying path 3 of the conveyor 2 with respect to the lamp 10A, and is curved along the circumferential direction around the axis of the lamp 10A. collects the infrared rays radiated to the opposite side, reflects them, and sends them to the conveyor 2 side. The reflector 10B is made of, for example, aluminum, stainless steel, or an aluminum-plated member.

Returning to FIG. 6, in step S03, the preprocessing unit 51 cuts out a characteristic wavelength region from the corrected spectrum S _cor (n, w). FIG. 8 is a diagram showing an example of a process of extracting a characteristic wavelength region from a reflected wave spectrum obtained when a black waste plastic piece is irradiated with infrared rays. The horizontal axis of FIG. 8 indicates the wavelength (nm) of the spectrum, and the vertical axis indicates the intensity of the spectrum at each wavelength. FIG. 8 shows an example of the spectrum of each material, acrylonitrile-butadiene-styrene (ABS), high-impact polystyrene (HIPS), polypropylene (PP), and polyethylene (PE). In the example of FIG. 8, spectra in the wavelength regions of 3250-3750 (nm) and 4400-4600 (nm) are cut out. Therefore, when sorting black plastics by material, the spectrum in at least one of the above ranges can be used.

Returning to FIG. 6, in step S04, the first determination unit 52 uses the spectrum corrected in step S02 and the characteristic wavelength region cut out in step S03 to determine whether each spectrum is the belt of the conveyor 2. (Conveyance path 3) or an object (waste plastic) on the conveyance path 3 is determined. The first determination unit 52 performs determination using the learned One Class SVM in this embodiment.

In step S05, the second determination unit 53 extracts two types of feature data Score1 and Score2 from the spectrum determined as the object (waste plastic) in step S04 using the learned PLS. FIG. 9 is a diagram showing an example of extraction of feature data. The horizontal axis of FIG. 9 indicates the first feature data (Score1), and the vertical axis indicates the second feature data (Score2). FIG. 9 shows an example of extraction of the four types of materials, ABS, HIPS, PP, and PE illustrated in FIG. As shown in FIG. 9, on the two-dimensional space of the two feature data Score1 and Score2, it can be seen that the areas plotted for each material can be divided. Note that the number of feature data may be other than two.

Returning to FIG. 6, in step S06, the third determination unit 54 determines the material using the learned decision tree based on the two types of feature data Score1 and Score2 extracted in step S5. FIG. 10 is a diagram showing an example of material discrimination using a decision tree. In this embodiment, in order to finally identify four types of materials (PE, PP, ABS, and HIPS), the decision tree has two levels of conditional branches as shown in FIG. In the first layer, a set of feature data Score1 and Score2 is divided into two groups G1 and G2 using a conditional branching function f1 (Score1, Score2). One group G1 is further divided into two groups G11 and G12 in the second hierarchy using a conditional branching function f2 (Score1, Score2). The other group G2 is further divided into two groups G21 and G22 in the second hierarchy using the conditional branching function f3 (Score1, Score2). As a result, the sets of feature data Score1 and Score2 are classified into four groups G11, G12, G21, and G22, and the material of each group is determined as PE, PP, ABS, and HIPS, respectively.

In this way, the discriminating device 5 of the waste plastic material judging and sorting device 1 according to the present embodiment detects reflected light of the light emitted to the conveying path 3 of the conveyor 2 by the illumination 10 detected by the mid-infrared camera 4. The first determination unit 52 determines whether the spectrum of the waste plastic piece S or the conveying path 3 is determined, and two types of feature data Score1 are obtained from the spectrum determined to be the waste plastic piece S by the first determination unit 52. , Score2, and a third determination unit 54 for determining the materials S1 and S2 of the waste plastic pieces S based on the characteristic data Score1 and Score2 extracted by the second determination unit 53.

With this configuration, the input information of the reflection spectrum is narrowed down to the spectrum of the black waste plastic piece S by the object discrimination of the first determination unit 52, and the dimension from the spectrum information to the feature data is obtained by the feature amount extraction of the second determination unit 53. Output information on the material of the waste plastic can be obtained through three stages of determination processing, compression and classification processing by the third determination unit 54, and data narrowing down. For this reason, the waste plastic sorting apparatus 1 of the present embodiment can determine the material of the waste plastic in consideration of various conditions, and can finely perform the determination over multiple stages. It is possible to improve the judgment accuracy of the material of

Further, the discriminating device 5 of the waste plastic sorting device 1 according to the present embodiment performs a first correction of the reflection spectrum S _org (n, w) detected by the mid-infrared camera 4 under conditions where the reflected light is bright. and a second correction spectrum D _ref (n, w) _measured under relatively darker conditions than this bright condition.

By correcting the reflection spectrum S _org (n, w) using the correction spectra W _ref (n, w) and D _ref (n, w), for example, using the equation (1), Differences in spectral intensity characteristics due to the effects of the temperature of the black waste plastic pieces S1 and S2 to be measured, the aging deterioration of the mid-infrared camera 4, the position on the conveyor 2, and the like can be suppressed. For this reason, the corrected spectrum S _cor (n, w) is used to perform learning and judgment by the first judging section 52, the second judging section 53, and the third judging section 54. Judgment accuracy can be further improved.

The preprocessing unit 51 further performs processing to cut out a predetermined frequency range from the corrected spectrum S _cor (n, w), and outputs the processed spectrum to the first determination unit 52 .

With this configuration, a portion strongly related to the material of the waste plastic can be extracted from the spectrum and used for learning and determination by the first determination unit 52, the second determination unit 53, and the third determination unit 54. It is possible to reduce the contamination of noise that hinders judgment and further improve the accuracy of judgment of the material of waste plastic.

Note that in the present embodiment, the preprocessing unit 51 performs two processes, that is, the process of correcting the reflection spectrum S _org (n, w) and the process of extracting a predetermined frequency range. It may be configured to perform.

Further, a method for sorting waste plastics of desired materials by the sorting apparatus 1 of the present embodiment will be described with reference to FIGS. 11 to 15. FIG. FIG. 11 is a plan view showing the first material sorting method by the sorting apparatus 1 of this embodiment. FIG. 11 shows a simplified view corresponding to the plan view of the sorting device 1 shown in FIG. From FIG. 11 onwards, as an example of the sorting method, an example in which a plastic mix in which waste plastic pieces of five types of materials (1), (2), (3), (4), and (5) are mixed is targeted for sorting. explain.

The example of FIG. 11 illustrates a configuration in which the conveyor 2 and the sorting section 12 are not divided in the width direction (y direction) of the conveyor 2 and a single transport path is formed. In the sorting unit 12, the waste plastics are sorted using the partition plate 9 shown in FIG. For this reason, in order to sort out the plastic mix in which the five types of materials to be sorted are mixed for each single material, one sorting unit 12-1 of the sorting unit 12 (for example, air is injected from the injection nozzle 7 It is necessary to repeat the process of separating waste plastics one by one. That is, as shown in FIG. 11, first, only waste plastic pieces of material (1) are sorted out from the plastic mix and collected by the sorting section 12-1. At this time, the other four types of materials (2) to (5) are mixed in the remaining plastic mixes collected in the other sorting section 12-2. Next, the remaining plastic mix in which the four types are mixed is put into the sorting device 1 again, and any one of the materials (2) to (5) is sorted. By repeating this procedure four times, waste plastic fragments of five types of materials (1) to (5) can be sorted by material.

FIG. 12 is a plan view showing a second material sorting method by the sorting apparatus 1A of this embodiment. From FIG. 12 onward, the transport path 3 of the conveyor 2 is divided into two systems, a first system and a second system, in the width direction. More specifically, each of the inlet (vibrating feeder 8), conveyor 2, and sorting section 12 is divided into two parts in the width direction. The input port 8 and the conveyor 2 are not made up of two constituent elements, but a single element with a partition or the like so as not to be mixed between systems. For example, the transport path 3 of the conveyor 2 can be divided into two systems by providing a partition wall along the transport direction at a substantially central position in the width direction.

In the following description, the first system is denoted by the subscript A and the second system by the subscript B. Elements corresponding to the sorting section 12-1 in FIG. It is written as "selecting unit B2".

In the example of FIG. 12, waste plastic pieces of the same material are collected in the first system and the second system. For example, as shown in FIG. 12, a plastic mix in which waste plastic pieces of five types of materials (1) to (5) are mixed is supplied to the inlets A and B of the first and second systems, respectively. , and waste plastic pieces of the same material (1) are collected in the sorting section A1 and the sorting section B1. Further, in the sorting section A2 and the sorting section B2, waste plastic pieces containing materials (2) to (5) other than the material (1) are collected.

FIG. 13 is a plan view showing a third material sorting method by the sorting apparatus 1B of this embodiment. In the example of FIG. 13, the first system collects the waste plastic pieces of the first material, supplies the remaining waste plastic pieces to the second system, and supplies the remaining waste plastic pieces to the second system. Collect waste plastic pieces of a second material from the inside. In the example of FIG. 13, a plurality of types of mixed materials can be classified into three types: first material, second material, and other materials.

In the example of FIG. 13, a plastic mix in which waste plastic pieces of five types of materials (1) to (5) are mixed is supplied to the inlet A of the first system, and the material is determined by the conveyor A of the first system. is performed, and waste plastic pieces of the material (1) are collected in the sorting section A1. Further, in the sorting section A2, waste plastic pieces containing the remaining materials (2) to (5) are collected.

Next, the waste plastic mixed with the remaining materials (2) to (5) collected in the sorting section A2 is conveyed to the input port B of the second system by the transport device 13, and supplied to the input port B. be. Material determination is performed on the conveyor B of the second system, and waste plastic pieces of material (2) are collected in the sorting section B1. In the sorting section B2, waste plastic pieces mixed with the remaining materials (3) to (5) are collected.

FIG. 14 is a plan view showing a fourth material sorting method by the sorting apparatus 1C of this embodiment. In the example of FIG. 14, the first system collects waste plastic pieces of the first material and a small amount of other materials, and supplies the collected waste plastic pieces to the second system. , collect the waste plastic pieces of the first material from among the waste plastic pieces of the first material and a small amount of other materials. In the example of FIG. 14, it is possible to sort plastic pieces of one kind of predetermined material with high purity.

In the example of FIG. 14, a plastic mix in which five types of materials (1) to (5) are mixed is supplied to the input port A of the first system, and the material judgment is performed on the conveyor A of the first system. The sorting section A1 collects waste plastic pieces of material (1) and a small amount of waste plastic pieces of materials (2) to (5). In the sorting section A2, waste plastics containing a mixture of the remaining materials (2) to (5) and a small amount of the material (1) are collected.

Next, the waste plastics containing the material (1) and a small amount of (2) to (5), which are collected in the sorting section A1, are transported by the transport device 13 to the input port B of the second system, and input. It is supplied to port B. The material is judged by the conveyor B of the second system, the material (1) is sorted again in the sorting section B1, and the waste plastic pieces of the material (1) are collected. The material (1) collected in the sorting section B1 has a higher purity than the material collected in the sorting section A1. In the sorting section B2, waste plastics mixed with the remaining materials (1) to (5) are collected.

FIG. 15 is a plan view showing a fifth material selection method by the sorting apparatus 1D of this embodiment. In the example of FIG. 15, in the first system, waste plastic pieces of the first material and a small amount of other materials are excluded, and the remaining waste plastic pieces are supplied to the second system. In the system, waste plastic pieces of the first material and a small amount of other materials are further excluded from other waste plastic pieces, and waste plastic pieces not containing the first material are collected. In the example of FIG. 15, it is possible to more reliably sort out plastic pieces of a predetermined kind of material from mixed materials.

In the example of FIG. 15, a plastic mix in which five types of materials (1) to (5) are mixed is supplied to the input port A of the first system, and the material judgment is performed on the conveyor A of the first system. Waste plastic pieces of material (1) and a small amount of materials (2) to (5) are collected in the sorting section A1. In the sorting section A2, waste plastics containing the remaining materials (2) to (5) mixed with a small amount of (1) are collected.

Next, the waste plastics mixed with the materials (2) to (5) and a small amount of (1) collected in the sorting section A2 are conveyed by the conveying device 13 to the input port B of the second system, and the input port supplied to B. Material judgment is performed on the conveyor B of the second system, and the material (1) is sorted again in the sorting section B1, and waste plastic pieces containing a mixture of the material (1) and a small amount of the materials (2) to (5) are produced. Collected. In the sorting section B2, waste plastics containing the remaining materials (2) to (5) and a small amount of (1) are collected.

FIG. 16 is a diagram showing an example of an operation screen of the sorting device 1. As shown in FIG. The operation screen shown in FIG. 16 is displayed on a display device installed in the material sorting apparatus 1, for example. As shown in FIG. 16, on the operation screen, the material names of the plastics to be sorted are listed, and the first system (“primary” in FIG. 16 and the second system (“secondary” in FIG. 15) ), the material to be ejected and sorted can be individually selected.The display device that displays the operation screen is, for example, a touch panel, and can be operated by pressing the "OFF" display in the "jet selection" column. By switching to the "ON" display, it is possible to set the ejection nozzles of the ejection nozzle row 7 to eject air and sort the material (ABS in FIG. 16) in the sorting section. It is also possible to provide a column "Area Ratio of Input Material" to display the ratio of each material mixed with the material according to the determination result of the material determination process.

In the above description, the waste plastic sorting apparatus is mainly described as including the surface treatment unit 20 for treating the surface of the waste plastic pieces. That is, another embodiment of the present invention is a waste plastic sorting apparatus comprising: an irradiation unit for irradiating surface-treated waste plastic pieces including black waste plastic pieces with light; a reflection spectrum detection unit that receives reflected light and detects the spectrum of the reflected light; a determination unit that determines the material of the waste plastic pieces based on the spectrum of the reflected light; and based on the result of the determination, The sorting device may include at least a sorting unit that sorts the black waste plastic pieces according to their materials. That is, the sorting device may be of a form into which waste plastic pieces that have already been surface-treated can be loaded. In this case, the surface of the surface-treated waste plastic piece has a glossiness (specular glossiness (%)) at an incident angle of 60° measured in accordance with JIS Z 8741 of 10 or less. The glossiness (specular glossiness (%)) at an incident angle of 75° measured by can be anything.

Another embodiment of the present invention is a method for sorting waste plastics, comprising: an irradiation step of irradiating surface-treated waste plastic pieces including black waste plastic pieces with light; a determination step of receiving reflected light to detect the spectrum of the reflected light and determining the material of the waste plastic pieces based on the spectrum of the reflected light; and determining at least black waste plastic pieces based on the result of the determination. It may be a sorting method including a sorting step of sorting according to the material.

(Example 1)
In this example, a group of black waste plastic pieces (plastic mix) was used as a sorting target. The size of each piece of plastic was about 5-30 mm in average diameter in plan view. The group of black waste plastic pieces used includes at least polyethylene (PE), polypropylene (PP), polycarbonate/acrylonitrile-butadiene-styrene (PCABS), acrylonitrile-butadiene-styrene (ABS), polystyrene (PS), and polyphenylene ether. /Polystyrene (PPEPS) and polyamide (PA) were included in the group of plastic fragments, but plastics other than the above seven plastics were also included. Such a group of black waste plastic pieces was sorted by material using a sorting device similar to the sorting device 1 shown in FIGS. The weight of the group of black waste plastic pieces used in one trial was 2.35 kg. Also, the conveyor speed of the sorting device was 120 to 150 m/min.

In the sorting device, infrared rays of 3 to 5 μm were irradiated and the spectrum of the reflected light was detected. Then, from the obtained reflected light spectrum, the spectra in the wavelength regions of 3250 to 3750 nm and 4400 to 4600 nm were cut out to obtain characteristic amounts, and based on the characteristic amounts, the material of the plastic was determined.

In the sorting apparatus used in this embodiment, an injection nozzle array in which 318 injection nozzles are arranged in a direction orthogonal to the conveying direction is provided. Discriminating devices in the sorting device include polyethylene (PE), polypropylene (PP), polycarbonate/acrylonitrile-butadiene-styrene (PCABS), acrylonitrile-butadiene-styrene (ABS), polystyrene (PS), polyphenylene ether/polystyrene (PPEPS). ), and polyamide (PA) could be registered. For each trial, it was possible to select one or more types of plastics to blow off (selectively blow) by injecting air from the injection nozzle.

Waste plastic was sorted by selective spraying according to trials 1-A and 1-1 to 1-7 shown below.

Trial 1-A: selective spraying of all seven plastics Trial 1-1: selective spraying of PE only Trial 1-2: selective spraying of PP only Trial 1-3: selective spraying of PCABS only Trial 1- 4: Selective spraying of ABS only Trial 1-5: Selective spraying of PS only Trial 1-6: Selective spraying of PPEPS only Trial 1-7: Selective spraying of PA only

<Measurement/Evaluation>
For the evaluation of sorting accuracy, the recovery rate R _A (%) of all seven types of plastics in the collected material obtained in Trial 1-A, various The plastic recovery rates R _PE , R _PP , ... (%), and the purities R _PE , R _PP , ... (%) of various plastics in the recovered materials obtained in trials 1-1 to 1-7 asked. Table 1 shows the results.

(Calculation of recovery rate _RA )
The recovery rates R _A (%) of all seven types of plastics in Trial 1-A were obtained as follows.

R _A (%) = W _A /W _L ×100
・W _L (kg): Input amount of waste plastic pieces (plastic mix) ・_WA (kg): Collected amount of all 7 types of waste plastic pieces (collected amount of plastic pieces blown off by selective spraying)

(Calculation of recovery rates R _PE , R _PP , ...)
The recovery rates R _PE , R _PP , . First, a group of waste plastic pieces having the content ratio and content of each material shown in Table 2 was prepared and each trial was conducted, and the recovery rate for each plastic type was determined based on the actually obtained recovery amount.

For example, R _PE in Trial 1-1 was obtained from the following formula:
_RPE (%) = _W1PE / _sWAPE x 100
・W1 _PE (kg): Actual amount of PE recovered in Trial 1-1 ・sWA _PE (kg): PE content (Table 2)
Similarly, recovery rates were determined for the other plastics of trials 1-2 to 1-7.

(Purity R _PE , R _PP , …)
The purities P _PE , P _PP , . These purities were obtained by using the plastic ratio determination function of the sorting apparatus by putting the plastic pieces collected after each trial of the sorting apparatus into the sorting apparatus again. For example, the purity P _PE in Trial 1-1 was the content ratio of PE measured by the plastic ratio determination function. The same was true for the other plastics in trials 1-2 through 1-7.

(Measurement of surface properties)
Glossiness (specular glossiness (%)) based on JIS Z 8741 was measured as the surface property of the plastic piece after the surface treatment. For the measurement, a gloss meter "VG 7000" manufactured by Nippon Denshoku Industries Co., Ltd. was used to measure the glossiness (specular glossiness (%)) at an incident angle of 60° and an incident angle of 75°. Furthermore, the surface roughness mean deviation (SMD) of the plastic piece after surface treatment was measured using an automated surface tester "KES-FB4-A" manufactured by Kato Tech Co., Ltd. Table 3 shows the measurement results of the surface properties of PCABS and PS as representative examples.

(Example 2)
The plastic pieces were sorted by material in the same manner as in Example 1, except that no surface treatment was performed. As in Example 1, selective spraying was performed according to trials 2-A and 2-1 to 2-7 shown below.

Trial 2-A: Selective spraying of all seven plastics Trial 2-1: Selective spraying of PE only Trial 2-2: Selective spraying of PP only Trial 2-3: Selective spraying of PCABS only Trial 2- 4: Selective spraying of ABS only Trial 2-5: Selective spraying of PS only Trial 2-6: Selective spraying of PPEPS only Trial 2-7: Selective spraying of PA only

The content ratio, content, recovery rate, and purity were obtained in the same manner as in Example 1. Tables 1 and 2 show the results. The surface properties of the plastic pieces before sorting were also determined in the same manner as in Example 1. Table 3 shows the results.

Table 1 lists selective spraying trials for all seven plastics (Trial 1-A in Example 1 and Trial 2-A in Example 2), as well as selective spraying trials for representative plastics (Trial 1 in Example 1). The results of Trials 1-3 to 1-6, and Trials 2-3 to 2-6 of Example 2) are shown by comparing Example 1 (with surface treatment) and Example 2 (without surface treatment). From these results, it was found that the recovery rate and purity of the plastic fragments were improved by surface treatment before sorting the waste plastic fragments. In particular, the glossiness at an incident angle of 60° measured in accordance with JIS Z 8741 (specular glossiness (%)) is 10 or less, and the glossiness at an incident angle of 75° measured in accordance with JIS Z 8741 (specular glossiness It was found that the recovery rate and purity of plastic fragments are improved by surface treatment so that the glossiness (%)) is 25 or less or the surface roughness mean deviation (SMD) is 1 μm or more.

The present embodiment has been described above with reference to specific examples. However, the present disclosure is not limited to these specific examples. Design modifications to these specific examples by those skilled in the art are also included in the scope of the present disclosure as long as they have the features of the present disclosure. Each element included in each specific example described above and its arrangement, conditions, shape, etc. are not limited to those illustrated and can be changed as appropriate. As long as there is no technical contradiction, the combination of the elements included in the specific examples described above can be changed as appropriate.

1, 1A, 1B, 1C, 1D Waste plastic sorting device 2 Conveyor 3 Conveying path 4 Mid-infrared camera (reflection spectrum detector)
5 Discrimination device 6 Injection control unit 7 Injection nozzle row 8 Vibration feeder 12, 12-1, 12-2, A1, A2, B1, B2 Sorting unit 20 Surface treatment unit 21, 22 Large rollers 23, 25 Rough surface roller 28 Supply Section 51 Pretreatment Section 52 First Judgment Section 53 Second Judgment Section 54 Third Judgment Section S, S1, S2 Waste plastic pieces (black waste plastic pieces)
S' Waste plastic piece before surface treatment

Claims (15)

A waste plastic sorting device,
a surface treatment unit for treating the surface of waste plastic pieces including black waste plastic pieces;
an irradiation unit for irradiating the surface-treated waste plastic piece with light;
a reflection spectrum detection unit that receives the reflected light of the irradiated light and detects the spectrum of the reflected light;
a determination unit that determines the material of the waste plastic pieces based on the spectrum of the reflected light;
A sorting device for waste plastics, comprising a sorting unit for sorting out at least black waste plastic pieces by material based on the result of the determination. In the surface treatment section, the surfaces of the waste plastic pieces are
(a) a specular gloss of 10% or less at an incident angle of 60° measured in accordance with JIS Z 8741;
(b) the specular gloss at an incident angle of 75° measured in accordance with JIS Z 8741 is 25% or less, and (c) the surface roughness average deviation (SMD) is 1 μm or more. 2. The waste plastic sorting apparatus according to claim 1, wherein the waste plastic is treated as follows. 3. The apparatus for sorting waste plastics according to claim 1, wherein the radiated light includes mid-infrared rays having a wavelength of more than 3 μm. The waste plastic pieces are conveyed on a conveying path,
The determination unit
a first determination unit that determines whether the spectrum of the reflected light is the spectrum of the waste plastic piece or the spectrum of the transport path;
a second determination unit that extracts a feature amount from the spectrum determined to be the spectrum of the waste plastic piece;
a third determination unit that determines the material of the waste plastic pieces based on the feature amount;
4. The waste plastic sorting apparatus according to claim 1, further comprising a sorting unit that sorts at least the black waste plastic pieces according to the material based on the result obtained by the third judging unit. The spectrum of the reflected light is a first correction spectrum obtained by measuring the reflected light under a bright condition, and a second correction spectrum obtained by measuring the reflected light under a dark condition darker than the bright condition. and a preprocessing unit that corrects using
5. The waste plastic sorting apparatus according to claim 4, wherein said first determination unit performs said determination using said spectrum corrected by said preprocessing unit. The preprocessing unit performs processing to cut out a predetermined frequency range from the corrected spectrum,
6. The waste plastic sorting apparatus according to claim 5, wherein the first determination unit uses the clipped spectrum to determine the material of the waste plastic piece. The waste plastic pieces are conveyed on a conveying path,
7. The apparatus for sorting waste plastics according to claim 6, wherein the transport path is divided into two systems, a first system and a second system, in the width direction of the transport path. 8. The waste plastic sorting apparatus according to claim 7, wherein waste plastic pieces of the same material are collected in said first system and said second system. The first system collects waste plastic pieces of a first material and supplies the remaining waste plastic pieces to the second system,
8. The waste plastic sorting apparatus according to claim 7, wherein said second system collects waste plastic pieces of a second material from said remaining waste plastic pieces. In the first system, waste plastic pieces of a first material and a small amount of other materials are collected, and the collected waste plastic pieces are supplied to the second system,
8. The waste plastic sorting apparatus according to claim 7, wherein said second system collects waste plastic pieces of the first material from among said first material and a small amount of waste plastic pieces of other materials. In the first system, waste plastic pieces of the first material and a small amount of other materials are excluded, and the remaining waste plastic pieces after the exclusion are supplied to the second system,
In the second system, waste plastic pieces of the first material and a small amount of other materials are further excluded from the remaining waste plastic pieces, and waste plastic pieces not containing the first material are collected. The waste plastic sorting apparatus according to claim 7, wherein A method for sorting waste plastic,
a surface treatment step of treating the surface of waste plastic pieces including black waste plastic pieces;
an irradiation step of irradiating the surface-treated waste plastic pieces with light;
a reflection spectrum detection step of receiving the reflected light of the irradiated light and detecting the spectrum of the reflected light;
a determination step of determining the material of the waste plastic pieces based on the spectrum of the reflected light;
and a sorting step of sorting at least the black waste plastic pieces by material based on the result of the determination. A waste plastic sorting device,
an irradiation unit that irradiates light to the surface-treated waste plastic pieces including the black waste plastic pieces;
a reflection spectrum detection unit that receives the reflected light of the light irradiated by the irradiation unit and detects the spectrum of the reflected light;
a determination unit that determines the material of the waste plastic pieces based on the spectrum of the reflected light;
A sorting device for waste plastics, comprising a sorting unit for sorting out at least black waste plastic pieces by material based on the result of the determination. The surface of the waste plastic piece is
(a) a specular gloss of 10% or less at an incident angle of 60° measured in accordance with JIS Z 8741;
(b) the specular gloss at an incident angle of 75° measured in accordance with JIS Z 8741 is 25% or less, and (c) the surface roughness average deviation (SMD) is 1 μm or more. 14. The waste plastic sorting apparatus according to claim 13, wherein the waste plastic is treated as follows. A method for sorting waste plastic,
an irradiation step of irradiating the surface-treated waste plastic pieces including the black waste plastic pieces with light;
receiving the reflected light of the irradiated light and detecting the spectrum of the reflected light;
a determination step of determining the material of the waste plastic pieces based on the spectrum of the reflected light;
and a sorting step of sorting at least the black waste plastic pieces by material based on the result of the determination.

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