CN115003425A

CN115003425A - Waste plastic material determination device, material determination method, and material determination program

Info

Publication number: CN115003425A
Application number: CN202180011546.5A
Authority: CN
Inventors: 大石升治; 村上孝伸
Original assignee: Daio Paper Corp
Current assignee: Daio Paper Corp
Priority date: 2020-02-13
Filing date: 2021-01-26
Publication date: 2022-09-02
Also published as: KR20220137627A; JP2021128062A; TW202136744A; WO2021161779A1; JP7419093B2

Abstract

A material quality determination device for waste plastics, comprising: a first determination unit that determines whether a spectrum of light emitted from the conveyor by the illumination device, the light being detected by the mid-infrared camera and being emitted to the conveyor on the conveying path, is a spectrum of the waste plastic sheet or a spectrum of the conveying path; a second determination unit that extracts two types of feature data from the spectrum determined by the first determination unit as the waste plastic sheet; and a third determination unit that determines the material of the waste plastic sheet based on the feature data extracted by the second determination unit.

Description

Waste plastic material determination device, material determination method, and material determination program

Technical Field

The present disclosure relates to a material quality determination device, a material quality determination method, and a material quality determination program for waste plastics.

Background

In order to recover materials in the reprocessing of waste plastics, it is required that the sorted products contain less non-target objects and have high purity. In addition, when expensive materials are included in the materials, it is required to be able to sort the expensive materials without missing them. Further, it is also required to efficiently perform material discrimination and sorting of black plastics which have conventionally been indiscriminately subjected to heat recovery, and to recover the materials.

Patent document 1 describes that an object to be picked is irradiated with infrared light and reflected light from the object to be picked is received, and the type of resin of the object to be picked is determined by a pattern matching method based on the spectrum of the reflected light.

< Prior Art document >

< patent document >

Patent document 1: japanese patent laid-open publication No. 2018-100903

Disclosure of Invention

< problems to be solved by the present invention >

However, in the conventional method described in patent document 1 and the like, there is room for improvement in the accuracy of material quality determination.

An object of the present disclosure is to provide a material quality determination device, a material quality determination method, and a material quality determination program, which can improve the accuracy of determining the material quality of waste plastics.

< means for solving the problems >

A material quality determination device for waste plastics according to an aspect of an embodiment of the present invention includes: an irradiation unit that irradiates the waste plastic sheet conveyed on the conveying path with light; a reflection spectrum detection unit that receives reflected light of the light irradiated by the irradiation unit to detect a spectrum of the reflected light; a first determination unit configured to determine whether the spectrum detected by the reflectance spectrum detection unit is a spectrum of the waste plastic sheet or a spectrum of the transport path; a second determination unit that extracts a feature amount from the spectrum determined by the first determination unit as the waste plastic sheet; and a third determination unit that determines the material of the waste plastic sheet based on the feature amount extracted by the second determination unit.

< effects of the invention >

According to the present invention, it is possible to provide a material quality determination device, a material quality determination method, and a material quality determination program that can improve the accuracy of determining the material quality of waste plastics.

Drawings

Fig. 1 is a perspective view showing a schematic configuration of a waste plastic material quality determination device according to an embodiment.

FIG. 2 is a side view of the waste plastic quality assessment device shown in FIG. 1.

FIG. 3 is a plan view of the waste plastic material quality determination apparatus shown in FIG. 1.

Fig. 4 is a functional block diagram of the determination device.

Fig. 5 is a flowchart of the material quality determination process for waste plastics according to the embodiment.

Fig. 6 is a diagram illustrating a method of extracting a spectrum for correction.

Fig. 7 is a diagram showing an example of a process of cutting out a wavelength region where a feature exists from a reflected wave spectrum.

Fig. 8 is a diagram showing an extraction example of feature data.

Fig. 9 is a diagram showing an example of material determination using a decision tree.

Fig. 10 is a plan view illustrating a first material sorting method by the material determination device of the present embodiment.

Fig. 11 is a plan view illustrating a second material sorting method by the material determination device of the present embodiment.

Fig. 12 is a plan view illustrating a third material sorting method by the material determination device of the present embodiment.

Fig. 13 is a plan view illustrating a fourth material sorting method by the material determination device of the present embodiment.

Fig. 14 is a plan view illustrating a fifth material sorting method by the material determination device of the present embodiment.

Fig. 15 is a diagram showing an example of an operation screen of the texture determination device.

Detailed Description

Hereinafter, embodiments will be described with reference to the drawings. In order to facilitate understanding of the description, the same reference numerals are given to the same components as much as possible in each drawing, and redundant description is omitted.

In the following description, the x direction, the y direction, and the z direction are perpendicular to each other. The x-direction and the y-direction are horizontal directions, and the z-direction is a vertical direction. The x direction is a conveying direction of the conveying path 3 of the conveyor 2. The y direction is the width direction of the conveying path 3 of the conveyor 2. For convenience of explanation, the positive z-direction side may be represented as the upper side and the negative z-direction side may be represented as the lower side.

The outline configuration of the waste plastic material quality determination device 1 according to the embodiment will be described with reference to fig. 1 to 3. Fig. 1 is a perspective view showing a schematic configuration of a waste plastic material quality determination device 1 according to an embodiment. Fig. 2 is a side view of the waste plastic material quality determination device 1 shown in fig. 1. Fig. 3 is a plan view of the waste plastic material quality determination device 1 shown in fig. 1. Here, a configuration example will be described in which two materials S1 and S2 (indicated by square and triangular marks in fig. 1 to 3) are mixed in the case where the waste plastics to be subjected to material quality determination are black waste plastics. Hereinafter, the black waste plastic pieces of the two materials S1 and S2 are sometimes collectively denoted by symbol S.

The material quality determination apparatus 1 of black waste plastics includes, as main components, a vibration feeder 8 as an example of a supply unit and a conveyor 2 as an example of a conveying unit, the vibration feeder 8 sequentially supplies black waste plastic pieces S1 and S2, and the conveyor 2 conveys the black waste plastic pieces S1 and S2 supplied from the vibration feeder 8. The crushed black waste plastic pieces S1 and S2 are supplied to the vibratory feeder 8 via a hopper for loading, for example. The vibration feeder 8 vibrates the mounting surface on which the black waste plastic sheets S1 and S2 are mounted, thereby supplying the black waste plastic sheets S1 and S2 to the conveyor 2 while preventing them from overlapping each other. The conveyor 2 has a conveying path 3 on its upper surface, and conveys the black waste plastic sheets S1, S2 on the conveying path 3 in a direction away from the vibratory feeder 8.

The material determination device 1 includes, as main components, an illumination device 10 as an example of an illumination unit, a mid-infrared camera 4 as an example of a reflectance spectrum detection unit, and a determination device 5, and the illumination device 10 irradiates infrared rays onto the black waste plastic sheets S1 and S2, the mid-infrared camera 4 detects reflectance spectra from the black waste plastic sheets S1 and S2, and the determination device 5 identifies the material of the black waste plastic sheets S1 and S2 based on the reflectance spectra detected by the mid-infrared camera 4. The lighting device 10 has a lamp 10A (see fig. 6) as an infrared light source such as a tungsten halogen lamp, and irradiates infrared rays from the lamp 10A to the black waste plastic sheets S1, S2. The illumination device 10 is provided so that the reflected light from the black waste plastic pieces S1 and S2 enters the mid-infrared camera 4 and is provided on both sides (or one side) above the mid-infrared camera 4 in the flow direction of the conveyor 2.

For example, as shown in fig. 1, the infrared camera 4 in 1 can measure across the entire region in the width direction of the conveyor 2, and can receive reflected light of near infrared rays from the black waste plastic sheet S1, S2 divided into a plurality of (for example, 318) regions in the width direction to measure the spectrum of the reflected light for each region. The mid-infrared camera 4 is composed of a spectrometer-equipped camera having a mid-infrared wavelength region of 3 μm or more, for example. The mid-infrared camera 4 performs measurement at a scanning frequency of, for example, 230Hz, and transmits 318 pieces of spectral data to the discrimination device 5 for each scanning. The determination device 5 outputs the material determination results of the 318 regions to the injection control unit 6, which will be described later, based on the 318 pieces of spectral data received from the mid-infrared camera 4.

The material quality determination device 1 is provided with a nozzle 7 for ejecting air from a lateral direction or an oblique direction in a direction intersecting the conveyance direction on the downstream side in the conveyance direction of the conveyor 2. A plurality of (e.g., 318) nozzles 7 are arranged in parallel in the width direction of the conveyor 2, and the operation of each nozzle is controlled by the injection control section 6. The ejection control unit 6 sorts the black waste plastic sheets S1 and S2 by ejecting air from the nozzles 7 or not ejecting air based on the material determination result received from the determination device 5, and drops the sorted sheets into a plurality of areas (e.g., collection hoppers) partitioned by the partition plates 9, for example, to collect waste plastics of a desired material. In other words, in the present embodiment, the ejection control unit 6, the nozzles 7, and the partition plate 9 function as the collecting device 12 for collecting waste plastic pieces of a desired material from the waste plastic pieces flowing through the conveying path 3 of the conveyor 2 based on the material determination result obtained by the determination device 5.

The operation of the material quality determination device 1 will be described. When the crushed black waste plastic pieces S1 and S2 are supplied to the vibration feeder 8 through a hopper for loading or the like, for example, the vibration feeder 8 conveys the supplied black waste plastic pieces S1 and S2 to the downstream side without overlapping them while applying vibration thereto, and supplies the black waste plastic pieces to the conveyor 2.

The black waste plastic sheets S1 and S2 fed to the conveying path 3 on the upper surface of the conveyor 2 are conveyed in the conveying direction on the x positive direction side, and are irradiated with infrared light from the illumination device 10 at a position where the mid-infrared camera 4 can take an image. The mid-infrared camera 4 receives the reflected light of the infrared rays emitted from the illumination device 10 reflected by the black waste plastic sheets S1, S2, and outputs the light reception result (data of the light reception spectrum) to the determination device 5.

The determination device 5 identifies the material of the black waste plastic sheets S1 and S2 based on the light reception result input from the mid-infrared camera 4. The details of the material determination method performed by the determination device 5 will be described later with reference to fig. 4 to 9. The determination device 5 outputs the material quality recognition result to the injection control unit 6.

The ejection control unit 6 selects a nozzle 7 corresponding to the material from among the plurality of arranged nozzles 7, measures the timing, and transmits a control signal. The nozzle 7 receiving the control signal opens the nozzle opening and ejects air. By ejecting air from the nozzles 7 at appropriate timing based on the determination result of the determination device 5, the material to be sorted and the material to be unsorted can be separated and collected.

In the example of fig. 2 and 3, the black waste plastic sheet S1 on the conveyor 2 is subjected to air from the air nozzle 7 that receives the control signal, blown down into the collecting device 12 provided for each material, and recovered. In addition, the black waste plastic pieces S2 on the conveyor 2 are not subjected to the air from the nozzles 7, and thus are collected into the collecting device 12 different from the black waste plastic pieces S1. By the ejection and stop of the nozzles 7 in this manner, the black waste plastic pieces of plural kinds of materials can be sorted and collected for each material.

A method for determining the material quality of waste plastics by the determination device 5 will be described with reference to fig. 4 to 9. Fig. 4 is a functional block diagram of the determination device 5.

As shown in fig. 4, the determination device 5 includes a preprocessing unit 51, a first determination unit 52, a second determination unit 53, and a third determination unit 54.

The preprocessing unit 51 performs preprocessing such as correction and processing on the reflection spectra of the black waste plastic sheets S1 and S2 detected by the mid-infrared camera 4. The preprocessing unit 51 corrects the detected reflection spectrum using, for example, a spectrum measured under a condition where the reflected light is bright and a spectrum measured under a condition where the reflected light is dark. "darker conditions" refer to relatively darker conditions as compared to the "lighter conditions" described above. In addition, the preprocessing section 51 performs processing of cutting out a predetermined frequency range from the corrected spectrum.

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

One Class SVM is an SVM as a classification algorithm for machine learning. In the SVM, a recognition boundary is set so that the euclidean distance is maximized, with a support vector of each class (located at a position closest to other classes in the training data) as a reference. In addition, in the case where the feature is a nonlinear feature, the data is mapped to the feature space using a kernel. By appropriately selecting the cores, the recognition boundary can be drawn even if the data arrangement is complicated.

In One Class SVM, a method called kernel trick is used for a Class of training data to map the data to a feature space of a high dimensional space. At this time, since the training data is mapped in such a manner as to be arranged away from the origin, data dissimilar to the original training data is gathered 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 One Class SVM having excellent pattern recognition capability for the first decision unit 52, it is possible to accurately discriminate whether the reflection spectrum is the spectrum reflected by the waste plastic sheets S1 and S2 or the spectrum reflected by the conveying path 3 of the conveyor 2. Note that a classification method of supervised learning, which is machine learning other than the One Class SVM, may be applied to the first determination unit 52.

The second determination unit 53 extracts feature data Score1 and Score2 (feature values) from the spectrum determined as the waste plastic pieces by the first determination unit 52. The second determination unit 53 performs determination using a learned PLS (Partial Least Squares).

PLS is a regression algorithm with supervised learning of machine learning, and regression analysis is performed between only a few principal components among the principal components calculated from explanatory variables and target variables. In PLS, the principal component is calculated so that the covariance with the target variable is large. In the present embodiment, two kinds of characteristic data Score1 and Score2 are calculated using PLS based on the explanatory variables of the reflection spectrum judged to be reflected by the waste plastic sheets S1 and S2.

By using PLS in the second determination unit 53, since the multidimensional interpretation variables of the reflectance spectrum can be reduced to a small number of features, appropriate feature data Score1 and Score2 that can be more easily distinguished can be extracted. Note that a multivariate analysis method of machine learning other than PLS may be applied to the second determination unit 53.

The third determination unit 54 determines the material of the waste plastic sheets S1 and S2 corresponding to the two characteristic quantities Score1 and Score2 of the reflection spectrum extracted by the second determination unit 53. The third determination unit 54 performs determination using the learned decision tree. A decision tree is a classification algorithm with supervised learning. Decision trees utilize a tree structure to represent rules for classifying target variables and are typically used for classification problems.

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

The determination device 5 may be physically configured as a computer system including a CPU (Central Processing Unit), a RAM (Random Access Memory) and a ROM (Read Only Memory) as main storage devices, a communication module, an auxiliary storage device, and the like. Each function of the determination device 5 shown in fig. 4 is realized by reading predetermined computer software (material determination program) into a CPU, a RAM, or the like, operating each hardware under the control of the CPU, and reading and writing data in the RAM. That is, the material quality determination program according to the present embodiment is executed on a computer, whereby the determination device 5 functions as the preprocessing unit 51, the first determination unit 52, the second determination unit 53, and the third determination unit 54 in fig. 4.

The material quality determination program according to the present embodiment is stored in a storage device provided in a computer, for example. The material determination program may be configured such that a part or the whole thereof is transmitted via a transmission medium such as a communication line and received and recorded (including installed) by a communication module or the like provided in the computer. The material determination program may be partially or entirely recorded (including installed) in the computer from a state of being stored in a removable storage medium such as a CD-ROM, a DVD-ROM, or a flash memory.

The determination device 5 may be a circuit including an analog circuit, a digital circuit, or an analog/digital hybrid circuit. Further, a control circuit for controlling each function of the determination device 5 may be provided. The respective circuits may be implemented by an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or the like.

Similarly, the injection control unit 6 may be physically configured as a computer system including a CPU, a RAM, a ROM, a communication module, an auxiliary storage device, and the like, and may realize the functions thereof by reading predetermined computer software into the CPU, the RAM, and the like.

Fig. 5 is a flowchart of the material quality determination process for waste plastics according to the embodiment. Each of the processes of the flowchart shown in fig. 5 is executed by the determination device 5.

In step S01, the spectrum S obtained by the mid-infrared camera 4 is acquired by the preprocessing unit 51 _org (n, w). Here, n is the number of sensors (the number of spectral detection regions divided in the width direction of the conveyor 2 by the mid-infrared camera 4), and when the number of sensors is 318, integers 0 to 317 corresponding to the respective detection regions are used. w is the wavelength of the spectrum, and in the present embodiment, a total of 131 wavelengths are set in increments of 20(nm) between 2700(nm) and 5300(nm), and integers of 0 to 130 corresponding to the respective wavelengths are used. In other words, S _org (n, w) represents the numerical value of the spectral intensity of the wavelength w in the nth spectral detection region in the width direction of the conveyor 2.

In step S02, the spectrum S acquired in step S01 is subjected to preprocessing by the preprocessing unit 51 _org (n, w) correcting, and calculating the corrected spectrum S _cor (n, w). By this correction, the black waste of the measurement object can be corrected by the concentration change of the water vapor and the carbon dioxide in the measurement spaceDifferences in the spectral intensity characteristics due to the temperature of the plastic sheets S1 and S2, the aging degradation of the illumination device 10 and the mid-ir camera 4, the position on the conveyor 2, and the like are absorbed. Corrected spectrum S _cor The (n, w) can be calculated by the following formula (1), for example.

[ number 1]

Here, W _ref (n, w) is a first calibration spectrum measured under the condition that the reflected light is bright. D _ref (n, w) is a second correction spectrum measured under the condition that the reflected light is darker than the above-described lighter condition. The spectra W for correction _ref (n，w)、D _ref The (n, w) may be extracted, for example, when the mid-infrared camera 4 is calibrated before the material discrimination processing is executed.

FIG. 6 shows a spectrum W for calibration _ref (n，w)、D _ref (n, w) extraction method. As shown in fig. 6, a calibration plate 11 for obtaining a spectrum for calibration is provided in an imaging area of the mid-infrared camera 4 on the conveyance path 3 of the conveyor 2, and the spectrum of the reflected light obtained by the mid-infrared camera 4 is detected, whereby a spectrum W for calibration can be obtained _ref (n，w)、D _ref (n，w)。

First correction spectrum W measured under the condition that reflected light is bright _ref In the case of (n, w), a calibration plate 11 (aluminum, stainless steel, or the like) for reflecting all wavelengths in the mid-infrared region is placed, and data of all wavelengths (w ═ 0(2700), 1(2720), 2(2740), …, 130(5300)) is acquired for all sensors (n ═ 0, 1, 2, …, 317) in a state where the illumination device 10 is turned on.

Second correction spectrum D measured under the condition that reflected light is dark _ref (n, w) in the case of the infrared camera, a calibration plate 11 (aluminum, stainless steel, etc.) for reflecting all wavelengths in the mid-infrared region is placed, and in a state where the lighting device 10 is turned off (or the camera is turned on)In a state where the door is closed, data of all wavelengths (w ═ 0(2700), 1(2720), 2(2740), …, 130(5300)) are acquired for all sensors (n ═ 0, 1, 2, …, 317).

The calibration plate 11 is preferably arranged so as to be able to obtain a spectrum W for calibration, as indicated by a broken-line arrow in fig. 6, for example _ref (n，w)、D _ref The position of the imaging area of the mid ir camera 4 on the conveying path 3 of the conveyor 2 arranged at the time of (n, w) and the standby position away from the imaging area of the mid ir camera 4 or the irradiation range of the illumination device 10 are moved. In other words, the calibration plate 11 is preferably capable of being fixed at a predetermined position within the field of view of the mid-infrared camera 4 and a predetermined position outside the field of view, and capable of moving between the two predetermined positions. The calibration plate 11 is preferably machined to have a surface roughness of a major surface receiving light from the illumination device 10 large and rough. This can suppress the occurrence of halation of reflected light.

Further, the conveyor 2 may be stopped when the spectrum for correction is acquired. In this case, if the calibration plate 11 is not correctly arranged at the position of the photographing region of the mid-infrared camera 4 due to some trouble in the action of the calibration plate 11, the temperature of the portion irradiated with the infrared ray on the conveying path 3 of the conveyor 2 may be increased due to the infrared ray of the illumination device 10, and may possibly cause burnout or ignition. Therefore, it is preferable to provide an interlock device so as not to emit infrared rays from the illumination device 10 when the calibration board 11 is not fixed in the field of view of the mid-infrared camera 4.

As shown in fig. 6, the lighting device 10 includes a lamp 10A (a sheath heater, a carbon lamp, a Kanthal lamp (Kanthal lamp), etc.) as an infrared light source, and a reflector 10B for collecting heat of the lamp 10A. The lamp 10A is formed to extend in the width direction (y direction) of the conveyor 2, and is arranged to emit infrared rays in all directions around the shaft center along the y axis. The reflecting plate 10B is disposed on the opposite side of the conveyor 2 from the conveyor path 3 with the lamp 10A as a reference, and is formed to be curved in the circumferential direction around the axis of the lamp 10A, whereby infrared rays emitted from the lamp 10A to the opposite side of the conveyor 2 can be collected, reflected, and sent to the conveyor 2 side. The reflection plate 10B is made of, for example, aluminum, stainless steel, or a member plated with aluminum or the like.

Returning to fig. 5, in step S03, the spectrum S is corrected by the preprocessing section 51 _cor (n, w) the wavelength region where the feature exists is cut out. Fig. 7 is a diagram showing an example of a process of cutting out a wavelength region where a feature exists from a reflected wave spectrum. In fig. 7, the horizontal axis represents the wavelength (nm) of the spectrum, and the vertical axis represents the intensity of the spectrum at each wavelength. Fig. 7 shows an example of spectra of ABS, HIPS, PP, PE of each material. In the example of FIG. 7, spectra in wavelength regions of 3250 to 3750(nm) and 4400 to 4600(nm) are cut out. In the example of fig. 7, the range of the cut-out wavelength region is shown by a hatching pattern.

Returning to fig. 5, in step S04, the first determination unit 52 determines whether each spectrum is the conveyor belt of the conveyor 2 (conveying path 3) or the object (waste plastic) on the conveying path 3, using the spectrum of the wavelength region corrected in step S02 and cut out in step S03 in which the feature exists. In the present embodiment, the first determination unit 52 performs determination using the One Class SVM after learning.

In step S05, the second decision unit 53 extracts two kinds of feature data Score1 and Score2 from the spectrum judged as the object (waste plastic) in step S4 using the learned PLS. Fig. 8 is a diagram showing an example of extraction of feature data. The horizontal axis of fig. 8 represents the first feature data (Score1), and the vertical axis represents the second feature data (Score 2). Fig. 8 shows an extraction example of the four materials ABS, HIPS, PP, PE illustrated in fig. 7. As shown in fig. 8, it can be seen that: in the two-dimensional space obtained from the two feature data Score1 and Score2, regions drawn for each material can be distinguished. The number of feature data may be other than two.

Returning to fig. 5, 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. 9 is a diagram showing an example of material determination using a decision tree. In the present embodiment, the decision tree has two layers of conditional branches as shown in fig. 9 in order to finally identify four materials (PE, PP, ABS, HIPS). In the first layer, the datasets of the characteristic data Score1, Score2 are divided into two groups G1, G2 using the function f1(Score1, Score2) of conditional branching. In the second layer, one of the groups G1 is further divided into two groups G11, G12 using a function f2(Score1, Score2) of conditional branching. In the second layer, the other group G2 was further divided into two groups G21, G22 using the function f3(Score1, Score2) of conditional branching. Therefore, the data sets of the feature data Score1 and Score2 are classified into four groups G11, G12, G21, and G22, and the material quality of each group is determined to be PE, PP, ABS, and HIPS, respectively.

As described above, the determination device 5 of the waste plastic material quality determination device 1 according to the present embodiment includes the first determination unit 52, the second determination unit 53, and the third determination unit 54, the first determination unit 52 determines whether the spectrum of the emitted light of the light irradiated to the conveyance path 3 of the conveyor 2 by the illumination device 10, which is detected by the mid-infrared camera 4, is the spectrum of the waste plastic pieces S or the spectrum of the conveyance path 3, the second determination unit 53 extracts two kinds of feature data Score1 and Score2 from the spectrum determined as the waste plastic pieces S by the first determination unit 52, and the third determination unit 54 determines the quality S1 and S2 of the waste plastic pieces S based on the feature data Score1 and Score2 extracted by the second determination unit 53.

With this configuration, output information of the material of the waste plastic can be obtained from the input information of the reflection spectrum through three stages of determination processing and data sorting, namely, sorting of the spectrum to the black waste plastic sheet S by object determination by the first determination unit 52, dimensional compression from the spectrum information to the feature data by feature amount extraction by the second determination unit 53, and sorting processing by the third determination unit 54. Therefore, the device 1 for determining the material quality of waste plastics according to the present embodiment can determine the material quality of waste plastics in consideration of various conditions, and can determine the material quality of waste plastics in detail in multiple stages, thereby improving the accuracy of determining the material quality of waste plastics.

In addition, according to the present embodimentThe discrimination apparatus 5 of the waste plastic material quality determination apparatus 1 of the embodiment includes a preprocessing unit 51, and the preprocessing unit 51 uses a first calibration spectrum W measured under a condition that reflected light is bright _ref (n, w) and a second correction spectrum D measured in a relatively darker condition than the brighter condition _ref (n, w) of the reflectance spectrum S detected by the mid-infrared camera 4 _org (n, w) correction is performed.

In this way, for example, using equation (1), the spectrum W for correction is used _ref (n, w) and D _ref (n, w) pair reflection spectrum S _org (n, w) are corrected so that the difference in the characteristics of the spectral intensity due to the influence of the temperature of the black waste plastic pieces S1, S2 as the object of measurement, the aged deterioration of the mid-infrared camera 4, the position on the conveyor 2, and the like can be suppressed. Thus, by using the corrected spectrum S _cor (n, w) the learning and determination of the first determination unit 52, the second determination unit 53, and the third determination unit 54 can be performed, thereby further improving the accuracy of determination of the material quality of the waste plastic.

In addition, the preprocessing section 51 further performs the spectrum S corrected from the spectrum S _cor (n, w) is processed in a predetermined frequency range, and the processed spectrum is output to the first determination unit 52.

With this configuration, since the portion having a strong relationship with the material quality 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 mixing of noise that hinders learning or determination, and to further improve the accuracy of determination of the material quality of the waste plastic.

Note that, in the present embodiment, the preprocessing unit 51 performs two processes, that is, the reflection spectrum S _org The correction processing of (n, w) and the process of cutting out a predetermined frequency range may be performed by only one of the two processes.

In the present embodiment, the case where the waste plastics to be evaluated for quality are black waste plastics S has been described as an example, but waste plastics of other colors such as red and blue may be used. Waste plastics of different colors may be used in combination.

A method of sorting waste plastics of a desired material by the material quality determination device 1 of the present embodiment will be described with reference to fig. 10 to 14. Fig. 10 is a plan view illustrating a first material sorting method performed by the material determination device 1 of the present embodiment. Fig. 10 is a simplified diagram corresponding to the plan view of the material determination device 1 shown in fig. 3. In the figures from fig. 10 onward, an example of a sorting method in which a plastic mixture containing 5 kinds of materials (1), (2), (3), (4), and (5) is used as a sorting target will be described.

In the example of fig. 10, a configuration in which one system of conveyance paths that are not divided in the width direction (y direction) of the conveyor 2 is formed on the conveyor 2 and the collecting device 12 is illustrated. In the collecting device 12, waste plastics are separated with the partition plate 9 shown in fig. 2 or the like as a boundary by the ejection and stop of the nozzles 7 to roughly classify the objects of sorting into two types. Therefore, in order to sort the plastic mixture, which is the object of sorting and contains 5 kinds of materials, for each single material, it is necessary to repeatedly perform the processing of one collecting device 12-1 (for example, a device for collecting waste plastic obtained by ejecting air from the nozzle 7) which is classified for each kind into the collecting devices 12. In other words, as shown in fig. 10, first, only the material (1) is sorted from the plastic mixture and recovered by the collection device 12-1. At this time, the remaining plastic mixture collected in the other collecting device 12-2 is mixed with the other 4 kinds of materials (2) to (5). Next, the remaining plastic mixture in which 4 kinds of the plastic mixtures were mixed was again charged into the material quality determination apparatus 1, and any one of (2) to (5) was classified. By repeating this step 4 times, 5 kinds of materials (1) to (5) can be distinguished.

Fig. 11 is a plan view illustrating a second material sorting method by the material determination device 1A of the present embodiment. In the figures after fig. 11, the conveying path 3 of the conveyor 2 is divided into two systems, a first system and a second system, in the width direction. More specifically, the inlet (the vibration feeder 8), the conveyor 2, and the collecting device 12 are each divided into two in the width direction. Note that, the inlet 8 and the conveyor 2 are not provided as two components, but a separator or the like is provided in a single component to prevent mixing between systems. For example, the conveying path 3 of the conveyor 2 may be divided into two systems by providing a partition wall in the conveying 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 is denoted by the subscript B. Elements corresponding to the collecting apparatus 12-1 in fig. 10 are referred to as "collecting apparatus a 1" and "collecting apparatus B1", and elements corresponding to the collecting apparatus 12-2 in fig. 10 are referred to as "collecting apparatus a 2" and "collecting apparatus B2".

In the example of fig. 11, waste plastic pieces of the same material are collected by the first system and the second system. For example, as shown in fig. 11, a plastic mixture in which 5 kinds of materials (1) to (5) are mixed is supplied to each inlet A, B of the first system and the second system, the material is determined in each system, and waste plastic pieces of the same material (1) are collected by each of collecting devices a1 and B1. In the collecting devices a2 and B2, waste plastics mixed with surplus materials (2) to (5) are collected.

Fig. 12 is a plan view illustrating a third material sorting method by the material determination device 1B of the present embodiment. In the example of fig. 12, waste plastic sheets of the 1 st material are collected in the 1 st system, and the remaining waste plastic sheets are supplied to the 2 nd system, and waste plastic sheets of the second material are collected from the remaining waste plastic sheets in the 2 nd system. In the example of fig. 12, the mixed material of plural types can be classified into 3 types of materials, i.e., the first material, the second material, and the other material.

In the example of fig. 12, a plastic mixture in which 5 types of materials (1) to (5) are mixed is supplied to the input port a of the 1 st system, the material is determined by the conveyor a of the 1 st system, and waste plastic pieces of the material (1) are collected in the collection device a 1. In the collecting device a2, waste plastics mixed with the surplus materials (2) to (5) are collected.

Then, the waste plastics mixed with the excess materials (2) to (5) collected in the collecting device a2 are conveyed to the inlet B of the second system by the conveying device 13 and supplied to the inlet B. The material quality determination was performed by the conveyor B of the second system, and waste plastic pieces of the material (2) were collected in the collecting device B1. In the collecting device B2, waste plastics mixed with the surplus materials (3) to (5) are collected.

Fig. 13 is a plan view illustrating a fourth material sorting method by the material determination device 1C of the present embodiment. In the example of fig. 13, in the first system, waste plastic sheets of a first material and a trace amount of other materials are collected, and the collected waste plastic sheets are supplied to the second system, and in the second system, waste plastic sheets of the first material are collected from waste plastic sheets of the first material and a trace amount of other materials. In the example of fig. 13, plastic sheets of a predetermined material can be sorted with high purity.

In the example of fig. 13, a plastic mixture of 5 types of materials (1) to (5) is supplied to the input port a of system 1, the material is determined by the conveyor a of system 1, and the material (1) and a small amount of waste plastic pieces (2) to (5) are collected in the collecting device a 1. In the collecting device a2, the remaining materials (2) to (5) and a small amount of waste plastics (1) were mixed and collected.

Then, the waste plastics mixed with the material (1) and the small amounts of (2) to (5) collected by the collecting device a1 are conveyed to the inlet B of the second system by the conveying device 13, and are supplied to the inlet B. The material quality determination is performed by the conveyor B of the second system, and the material (1) is sorted again by the collecting device B1 to collect the waste plastic pieces of the material (1). The purity of the material (1) collected by the collecting apparatus B1 was higher than that of the material collected by the collecting apparatus a 1. In the collecting device B2, waste plastics mixed with the surplus materials (1) to (5) are collected.

Fig. 14 is a plan view illustrating a fifth material sorting method by the material determination device 1D of the present embodiment. In the example of fig. 14, the first system removes waste plastic pieces of the first material and a small amount of other materials, and supplies the remaining waste plastic pieces after removal to the second system, and the second system further removes waste plastic pieces of the first material and a small amount of other materials from other waste plastic pieces to collect waste plastic pieces not containing the first material. In the example of fig. 14, a plastic sheet of a predetermined material can be selected from the mixed material more reliably.

In the example of fig. 14, a plastic mixture in which 5 types of materials (1) to (5) are mixed is supplied to the input port a of the first system, the material is determined by the conveyor a of the first system, and the material (1) and a small amount of waste plastic pieces (2) to (5) are collected by the collecting device a 1. In the collecting device a2, the remaining materials (2) to (5) and a small amount (1) of waste plastics were mixed and collected.

Then, the waste plastics mixed with the materials (2) to (5) and the small amount (1) collected by the collecting device a2 are conveyed to the inlet B of the second system by the conveying device 13, and supplied to the inlet B. The material quality determination was performed by the conveyor B of the second system, and the material (1) was sorted again by the collecting device B1 to collect waste plastic pieces in which the material (1) and the minute amounts of the materials (2) to (5) were mixed. In the collecting apparatus B2, the waste plastics in which the surplus materials (2) to (5) and the small amount (1) are mixed are collected.

Fig. 15 is a diagram showing an example of an operation screen of the material determination device 1. The operation screen shown in fig. 15 is displayed on a display device provided in the main body of the material determination device 1, for example. As shown in fig. 15, on the operation screen, the names of the materials of the plastics to be sorted are listed, and the materials to be sorted can be individually selected by performing the ejection in accordance with the above-described first system ("primary" in fig. 15) and second system ("secondary" in fig. 15), respectively. The display device displaying the operation screen is, for example, a touch panel, and may be set so that the nozzle 7 is caused to eject air and the collection device is differentiated in the case of the material (ABS in fig. 15) by switching to the "ON" display by an operation such as pressing the "OFF" display of the "ejection selection" column. Further, on the operation screen, "input material area ratio" may be set, and the ratio of each material mixed in the material may be displayed based on the determination result of the material determination process.

The present embodiment has been described above with reference to specific examples. However, the present disclosure is not limited to these specific examples. Embodiments obtained by appropriately modifying the design of these specific examples by those skilled in the art are also included in the scope of the present disclosure as long as the features of the present disclosure are provided. The elements, the arrangement, conditions, shapes, and the like of the elements included in the specific examples are not limited to those of the illustrated embodiments, and may be modified as appropriate. The combination of the elements provided in the above-described specific examples may be appropriately changed as long as no technical contradiction is generated.

The international application is based on Japanese patent application No. 2020-.

Description of the symbols

1. 1A, 1B, 1C, 1D: a waste plastic material quality determination device;

2: a conveyor;

3: a conveying path;

4: a mid-infrared camera (reflectance spectrum detection section);

5: a discrimination device;

51: a pretreatment section;

52 a first judgment unit;

53: a second judgment section;

54: a third judgment unit;

12. 12-1, 12-2, A1, A2, B1, B2: a collection device;

s1, S2: black waste plastic pieces.

Claims

1. A material quality determination device for waste plastics, comprising:

an irradiation unit that irradiates the waste plastic sheet conveyed on the conveying path with light;

a reflection spectrum detection unit that receives reflected light of the light irradiated by the irradiation unit to detect a spectrum of the reflected light;

a first determination unit configured to determine whether the spectrum detected by the reflectance spectrum detection unit is a spectrum of the waste plastic sheet or a spectrum of the transport path;

a second determination unit that extracts a feature amount from the spectrum determined by the first determination unit as the waste plastic sheet; and

and a third judging section for judging the material of the waste plastic sheet based on the feature amount extracted by the second judging section.

2. The device for determining the quality of waste plastic according to claim 1, further comprising:

a preprocessing section that corrects the spectrum detected by the reflectance spectrum detection section using a first correction spectrum measured under a condition that the reflected light is bright and a second correction spectrum measured under a condition that the reflected light is darker than the bright condition,

wherein the first judging section performs the judgment using the spectrum corrected by the preprocessing section.

3. The quality determination apparatus of waste plastics according to claim 2, wherein,

the preprocessing section performs processing of cutting out a predetermined frequency range from the corrected spectrum,

the first judging section performs the judgment using the spectrum processed by the preprocessing section.

4. The quality determination device of waste plastics according to any one of claims 1 to 3, wherein,

the first determination unit performs determination using a learned One Class SVM.

5. The quality determination device of waste plastic according to any one of claims 1 to 4, wherein,

the second determination unit performs determination using the learned PLS.

6. The quality determination device of waste plastic according to any one of claims 1 to 5, wherein,

the third determination unit performs determination using the learned decision tree.

7. The device for determining the quality of waste plastic according to any one of claims 1 to 6, further comprising:

a collecting device for collecting waste plastic pieces of one material from the waste plastic pieces flowing through the conveying path based on the determination result of the third determining unit.

8. The quality determination apparatus of waste plastics according to claim 7, wherein,

the conveying path is divided into two systems, a first system and a second system, in the width direction.

9. The quality determination apparatus of waste plastics according to claim 8, wherein,

collecting waste plastic pieces of the same material in the first system and the second system.

10. The quality determination apparatus of waste plastics according to claim 8, wherein,

in the first system, waste plastic sheets of a first material are collected and the remaining waste plastic sheets are supplied to the second system,

in the second system, waste plastic pieces of a second material are collected from the remaining waste plastic pieces.

11. The quality determination apparatus of waste plastics according to claim 8, wherein,

collecting waste plastic pieces of a first material and a trace amount of other materials in the first system, and supplying the collected waste plastic pieces to the second system,

in the second system, waste plastic pieces of the first material are collected from the waste plastic pieces of the first material and a trace amount of other materials.

12. The quality determination apparatus of waste plastics according to claim 8, wherein,

in the first system, waste plastic pieces of a first material and a trace amount of other materials are removed, and the remaining waste plastic pieces after removal are supplied to the second system,

in the second system, the waste plastic pieces of the first material and a trace amount of the other materials are further removed from the other waste plastic pieces to collect waste plastic pieces not containing the first material.

13. A method for determining the quality of waste plastic, comprising:

an irradiation step of irradiating light on the waste plastic sheet conveyed on the conveying path;

a reflected spectrum detection step of receiving reflected light of the light irradiated in the irradiation step to detect a spectrum of the reflected light;

a first determination step of determining whether the spectrum detected in the reflection spectrum detection step is a spectrum of the waste plastic sheet or a spectrum of the transport path;

a second determination step of extracting a feature amount from the spectrum determined as the waste plastic sheet in the first determination step; and

a third determination step of determining a material of the waste plastic sheet based on the feature amount extracted in the second determination step.

14. A material quality judging program for waste plastics, which causes a computer to realize the following functions:

an irradiation function of irradiating the waste plastic sheet conveyed on the conveying path with light;

a reflected spectrum detection function of receiving reflected light of the light irradiated by the irradiation function to detect a spectrum of the reflected light;

a first determination function of determining whether the spectrum detected by the reflectance spectrum detection function is a spectrum of the waste plastic sheet or a spectrum of the transport path;

a second determination function of extracting a feature amount from the spectrum determined as the waste plastic sheet by the first determination function; and

and a third determination function of determining a material of the waste plastic sheet based on the feature amount extracted by the second determination function.