Sorting and Processing System

Abstract

The sorting processing system of the present disclosure comprises a first detection unit that acquires first raw material information, a second detection unit that acquires second raw material information, a calculation unit having an analytical model that outputs a setting value related to the sorting conditions, and a control unit that changes the sorting conditions of the sorting device, wherein the calculation unit processes the first raw material information for each first processing cycle, and processes the second raw material information for each second processing cycle that is longer than the first processing cycle, and switches between a first analysis method in which the first raw material information is input into the analytical model and the setting value is output, and a second analysis method in which at least the second raw material information is input into the analytical model and the setting value is output.

Description

[Technical field]

[0001] The present disclosure relates to a sorting system. [Background technology]

[0002] Patent Document 1 discloses a technology for sorting mixtures of plastic pieces, etc. In such sorting, the state of the raw materials, such as the raw material composition ratio or specific charge, is detected, and sorting conditions are determined based on the results. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] International Publication No. 2012 / 101874 Summary of the Invention [Problem to be solved by the invention]

[0004] The raw material state may vary over time. To accommodate such variations, the raw material state is acquired at regular time intervals. In a configuration for detecting multiple types of raw material states, the period for acquiring data required to determine the sorting conditions may differ for each raw material state. In this case, the accuracy of sorting is affected by how the multiple types of raw material states acquired at different periods are used to determine the sorting conditions.

[0005] In view of the above circumstances, an object of the present disclosure is to provide a sorting processing system capable of ensuring sorting accuracy in a configuration in which multiple types of raw material states are acquired at different cycles. [Means for solving the problem]

[0006] One aspect of the sorting processing system according to the present disclosure includes a sorting device that sorts a mixture containing multiple types of objects by type of object, a first detection unit that acquires first raw material information about the mixture input to the sorting device, a second detection unit that acquires second raw material information of a different type from the first raw material information about the mixture input to the sorting device, a calculation unit having an analytical model that outputs a setting value for a sorting condition of the sorting device, and a control unit that changes the sorting condition of the sorting device based on the setting value output by the calculation unit, wherein the calculation unit processes the first raw material information every first processing cycle and processes the second raw material information every second processing cycle that is longer than the first processing cycle, and the calculation unit switches between a first analysis method in which the first raw material information is input to the analytical model and the setting value is output, and a second analysis method in which at least the second raw material information is input to the analytical model and the setting value is output. Effect of the Invention

[0007] According to the sorting processing system of the present disclosure, in a configuration in which multiple types of raw material states are acquired at different cycles, it is possible to ensure sorting accuracy. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram illustrating an example of a configuration of a sorting processing system according to a first embodiment. [Diagram 2] 2 is a diagram illustrating an example of the configuration of a first detection unit and a second detection unit in FIG. 1. [Diagram 3] FIG. 1 is a diagram explaining a method for acquiring a raw material composition ratio using HSI data from a hyperspectral camera. [Figure 4] FIG. 2 is a diagram illustrating a first analysis method and a second analysis method. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Embodiment 1 Hereinafter, an embodiment of the present disclosure will be described with reference to the drawings. Note that the scope of the present disclosure is not limited to the following embodiment, and can be modified as desired within the scope of the technical concept of the present disclosure. FIG. 1 is a configuration diagram illustrating a sorting processing system 1 in embodiment 1. The sorting processing system 1 has a first detection unit 11, a sorting device 12, a calculation unit 13, a control unit 14, and a second detection unit 21.

[0010] The sorting processing system 1 is configured to sort a mixture containing multiple types of objects by object type. In this embodiment, a plastic piece group P will be described as an example of a "mixture containing multiple types of objects." In the example of FIG. 1, the plastic piece group P contains two types of plastic pieces p1 and p2 that are made of different materials. In this specification, the plastic pieces p1 and p2 may be referred to as "flakes" without distinguishing between the materials. Three or more types of plastic pieces may be included in the plastic piece group P.

[0011] In the following, an example will be described in which the plastic piece p1 is ABS and the plastic piece p2 is PS. The plastic pieces p1 and p2 are obtained, for example, by crushing the housing of a home appliance with a crusher and drying it. The plastic pieces p1 and p2 are formed to a size of, for example, about 10 mm square.

[0012] The sorting device 12 sorts the plastic pieces p1 and p2 by type through electrostatic sorting. In the example of Fig. 1, the sorting device 12 includes an input section 121, a charging cylinder 122, a vibration feeder 123, a first electrode 124, a second electrode 125, a DC power source 126, a collection box 127, and partition plates 128 and 129. However, the configuration of the sorting device 12 in Fig. 1 is merely an example and can be changed.

[0013] The sorting device 12 can electrostatically sort a plastic piece group P, which is a mixture of multiple types of plastic pieces p1 and p2 having different charging characteristics, into plastic pieces p1 and plastic pieces p2.

[0014] The input section 121 includes a hopper 121a and an input feeder 121b. Dried plastic piece group P is supplied to the hopper 121a. The hopper 121a supplies a predetermined amount of the plastic piece group P per unit time to the input feeder 121b. The input feeder 121b supplies the plastic piece group P input from the hopper 121a into the charging cylinder 122.

[0015] The charging cylinder 122 and the vibrating feeder 123 constitute the charging unit. The charging unit charges each of the plastic pieces p1, p2 and causes them to fall. Specifically, the charging cylinder 122 agitates the plastic piece group P by rotating. Inside the charging cylinder 122, the multiple types of plastic pieces p1, p2 mixed in the plastic piece group P rub against each other and become charged. Each of the charged plastic pieces p1, p2 has a charge of a polarity (positive or negative) according to the triboelectric series. In this example, the plastic piece p1, which is ABS, is positively charged, and the plastic piece p2, which is PS, is negatively charged.

[0016] The electrically charged plastic pieces p1 and p2 are supplied to the rear end of the upper surface of the vibrating feeder 123. The positively charged plastic piece p1 and the negatively charged plastic piece p2 are attracted to each other by electrostatic force and are paired. The vibrating feeder 123 pushes the plastic pieces p1 and p2 forward while vibrating them up and down. This releases the pairing of the plastic pieces p1 and p2, and the plastic pieces p1 and p2 move forward in the X direction in the figure. The plastic pieces p1 and p2 also fall from the vibrating feeder 123.

[0017] The electrodes 124, 125 and the DC power supply 126 constitute an electric field generating unit. The electric field generating unit applies an electrostatic field to each charged plastic piece, causing each plastic piece to fall at a position according to the charged state of each plastic piece. Specifically, the electrodes 124, 125 are formed in a flat plate shape. The electrodes 124, 125 are arranged in the X direction in the figure, and are arranged opposite each other so as to sandwich the path along which the plastic pieces p1, p2 fall. A ground voltage GND is applied to the first electrode 124. The DC power supply 126 applies a predetermined DC voltage between the first electrode 124 and the second electrode 125, generating an electrostatic field between the first electrode 124 and the second electrode 125.

[0018] When the plastic pieces p1 and p2, which have been unpaired by the vibrating feeder 123, are dropped between the electrodes 124 and 125, each plastic piece falls while being attracted to either the electrode 124 side or the electrode 125 side by electrostatic force according to its charged state (polarity, amount of charge). That is, each plastic piece p1 and p2 draws a parabolic trajectory according to its charged state and falls in a different position. In this example, the plastic piece p1 is positively charged and therefore falls on the first electrode 124 side. On the other hand, the plastic piece p2 is negatively charged and therefore falls on the second electrode 125 side.

[0019] Collection box 127 is provided below electrodes 124, 125, and collects plastic pieces p1, p2 that have passed between electrodes 124, 125 from vibrating feeder 123 and dropped therefrom. Collection box 127 is formed in a rectangular parallelepiped shape with an opening at the top. The opening of collection box 127 is formed in a rectangular shape with its long side facing the X direction in the figure.

[0020] Each of the partition plates 128, 129 is also referred to as a partition member. The partition plates 128, 129 are arranged in the recovery box 127 parallel to the YZ plane in the figure, and are provided so as to be movable in the X direction in the figure. The positions of the partition plates 128, 129 in the X direction are controlled by the control unit 14. The partition plate 128 is located on the first electrode 124 side, and the partition plate 129 is located on the second electrode 125 side. The recovery box 127 is divided by the partition plates 128, 129 into a recovery chamber 127a on the first electrode 124 side, a recovery chamber 127b on the second electrode 125 side, and a middle recovery chamber 127c.

[0021] Each of the plastic pieces p1 and p2 that drop from the vibrating feeder 123 after passing between the electrodes 124 and 125 is collected in one of the three collection chambers 127a to 127c depending on its charge state. In this example, the plastic piece p1 is positively charged and is collected in the collection chamber 127a. On the other hand, the plastic piece p2 is negatively charged and is collected in the collection chamber 127b. The plastic pieces p1 and p2 that are not sufficiently charged are collected in the collection chamber 127c.

[0022] The plastic pieces p1 collected in collection chamber 127a, the plastic pieces p2 collected in collection chamber 127b, and the plastic pieces p1 and p2 collected in collection chamber 127c are transported by a conveying machine (not shown) and stored in separate containers.

[0023] The first detection unit 11 acquires first raw material information. The first raw material information is, for example, a raw material composition ratio. When acquiring the raw material composition ratio, the first detection unit 11 includes, for example, a hyperspectral camera 11a and a processing unit 11b as shown in FIG. 2. The hyperspectral camera 11a captures an image of the plastic piece group P flowing on the vibration feeder 123 by a line scan method. The hyperspectral camera 11a performs line scanning on the plastic piece group P conveyed by the vibration feeder 123 at a constant speed, for example, at about 500 fps.

[0024] The hyperspectral camera 11a separates light emitted from each point of the subject, the group of plastic pieces P, and captures it on the sensor surface. A plurality of pixels are arranged on the sensor surface, and each pixel captures light of a different wavelength. The hyperspectral camera 11a outputs HSI data based on the intensity of light of each wavelength. HSI is an abbreviation for hyperspectral imaging. The HSI data contains near-infrared spectral information for each pixel.

[0025] FIG. 3 shows an example of acquiring a raw material composition ratio using HSI data of the hyperspectral camera 11a. As shown in FIG. 3(A), the HSI data includes spectrum information for each pixel associated with the shape of the flakes on the vibrating feeder 123. Points (i) and (ii) are parts of the flakes, and point (iii) is part of the vibrating feeder 123. FIG. 3(A1) shows the spectrum for each pixel of points (i) to (iii). In each graph of FIG. 3(A1), for example, the horizontal axis is wavelength, and the vertical axis is intensity for each wavelength.

[0026] The processing unit 11b of the first detection unit 11 processes the HSI data generated by the hyperspectral camera 11a. The processing unit 11b analyzes the HSI data and generates an image in which the flakes included in the plastic piece group P are color-coded according to the plastic material. FIG. 3(B) is an example of an image generated by analyzing the HSI data of FIG. 3(A). In the image of FIG. 3(B), the flakes including point (i) are displayed in red, and the flakes including point (ii) are displayed in blue. In the image of FIG. 3(B), for example, the red flakes are plastic pieces p1, and the blue flakes are plastic pieces p2. Furthermore, the processing unit 11b performs image analysis to determine the area ratio of each color and converts it into a raw material composition ratio. In the example of FIG. 3(B), the ratio of the area of ​​the red region to the area of ​​the blue region is 60:40. Therefore, it can be determined that the raw material composition ratio of the plastic piece p1 is 60%, and the raw material composition ratio of the plastic piece p2 is 40%. In this manner, the first detection unit 11 sequentially measures the raw material composition ratio of the plastic piece group P conveyed by the vibrating feeder 123 by the line scan method.

[0027] The second detection unit 21 acquires second raw material information, which is different from the first raw material information. The second raw material information is, for example, specific charge. When acquiring specific charge, the second detection unit 21 includes, for example, a charge amount sensor 21a and a weight sensor 21b as shown in FIG. 2. Specifically, the flakes conveyed on the vibrating feeder 123 are picked up one by one, and the charge amount and weight are measured by the charge amount sensor 21a and the weight sensor 21b. The specific charge of the flake can be measured by dividing the charge amount by the weight.

[0028] The first detection unit 11 inputs the acquired first raw material information to the calculation unit 13. The second detection unit 21 inputs the acquired second raw material information to the calculation unit 13. The calculation unit 13 is equipped with an analysis model that outputs set values ​​for the sorting conditions of the sorting device 12. This analysis model analyzes the set values ​​of the sorting conditions based on at least one of the first raw material information and the second raw material information so as to obtain optimal sorting accuracy. The analysis model of the calculation unit 13 may use, for example, multiple regression analysis. In addition, the analysis model of the calculation unit 13 may use machine learning. These analysis models output set values ​​of the sorting conditions suitable for the current raw material information by performing analysis based on a combination of past raw material information, set values ​​of the sorting conditions, and sorting accuracy.

[0029] The set values ​​of the sorting conditions, which are the analysis results of the calculation unit 13, are input to the control unit 14. The control unit 14 controls the sorting conditions of the sorting device 12 based on the set values ​​input from the calculation unit 13. For example, the control unit 14 may control the positions of the partition plates 128 and 129 in the X direction. Alternatively, the control unit 14 may control the rotation speed or inclination of the charging cylinder 122, the voltage applied by the DC power supply 126 to the second electrode 125, and the like. In other words, the "set values" are the positions of the partition plates 128 and 129 in the X direction, the rotation speed or inclination of the charging cylinder 122, the voltage of the DC power supply 126, and the like. The "set values" may include a plurality of these parameters.

[0030] Here, the calculation unit 13 processes the first ingredient information acquired by the first detection unit 11 based on the "first processing cycle". Also, the calculation unit 13 processes the second ingredient information acquired by the second detection unit 21 based on the "second processing cycle". The first processing cycle and the second processing cycle are determined based on the requested data amount for the first ingredient information and the second ingredient information. The "requested data amount" is the data amount of the first ingredient information and the second ingredient information required for the calculation unit 13 to analyze the setting values ​​of the sorting conditions. The requested data amount is determined by the variability of the measurement data of the first ingredient information and the second ingredient information. The greater the variability of the measurement data, the more requested data amount is required to ensure sorting accuracy.

[0031] As an example, when calculating the set value of the sorting condition based on the raw material composition ratio, a data amount of 500 flakes is required to ensure sorting accuracy. In the line scan method, for example, the raw material composition ratio of 1000 flakes can be obtained per minute. In this example, the period for obtaining the required data amount, i.e., "raw material composition ratio of 500 flakes", is 30 seconds. Therefore, the "first processing period" in this example is 30 seconds.

[0032] As an example, when calculating the set value of the sorting condition based on the specific charge, a data amount of 200 flakes is required to ensure sorting accuracy. In the picking method, for example, the specific charge of 10 flakes can be obtained per minute. In this example, the period during which the required data amount, i.e., the "specific charge of 200 flakes," can be obtained is 20 minutes. Therefore, the "second processing period" in this example is 20 minutes.

[0033] As described above, the first raw material information and the second raw material information include measurement data for a plurality of flakes. The calculation unit 13 statistically processes the measurement data to obtain statistical values ​​such as average values ​​or median values. The calculation unit 13 inputs such statistical values ​​into an analysis model to output setting values ​​for the sorting conditions. Note that the specific values ​​of the first processing cycle, the second processing cycle, the requested data amount, and the like described above are merely examples and can be changed. However, in the present disclosure, the first processing cycle is shorter than the second processing cycle.

[0034] Here, the first raw material information has an advantage that, since the first processing cycle is short, if there is a fluctuation point in the mixture to be input, it is easy to detect. The "fluctuation point" is, for example, a fluctuation in the type of home appliance that is the source of the mixture to be input to the sorting device 12. It is expected that the first raw material information and the second raw material information will fluctuate significantly before and after the fluctuation point. Due to the long second processing cycle, the second raw material information is likely to include data before and after the fluctuation point. It is considered that if the setting value of the sorting condition is determined based on the second raw material information that includes data before and after the fluctuation point in this way, the sorting accuracy will decrease.

[0035] On the other hand, the raw material composition ratio, which is an example of the first raw material information, has a low correlation with the sorting accuracy such as the recovery rate and purity. The specific charge, which is an example of the second raw material information, has a high correlation with the sorting accuracy compared to the raw material composition ratio. Therefore, by determining the setting values ​​of the sorting conditions using the second raw material information as much as possible, the sorting accuracy can be further improved.

[0036] In consideration of the above circumstances, the calculation unit 13 in this embodiment switches the analysis method when outputting the setting values ​​of the sorting conditions, as shown in Fig. 4. In the "first analysis method" shown in Fig. 4(b), the calculation unit 13 inputs the first ingredient information into the analysis model without using the second ingredient information, and outputs the setting values ​​of the sorting conditions. In the "second analysis method" shown in Fig. 4(c), the calculation unit 13 inputs both the first ingredient information and the second ingredient information into the analysis model, and outputs the setting values ​​of the sorting conditions.

[0037] FIG. 4(a) is an example of a graph showing the fluctuations of the first and second raw material information in a time series. In FIG. 4(a), the plots of the first and second raw material information show the statistical values ​​of the required data amount calculated for each processing cycle. In this example, the "statistical value" is an average value, but instead of the average value, a median value or the like may be used. In FIG. 4(a), the raw material composition ratio is exemplified as the first raw material information, and the specific charge is exemplified as the second raw material information. At time t1, the statistical values ​​of the first raw material information for the required data amount are obtained, but the statistical values ​​of the second raw material information for the required data amount are not obtained. Therefore, the calculation unit 13 outputs the setting values ​​of the sorting conditions by the "first analysis method" during the period from time t1 to t2.

[0038] At time t2 in Fig. 4(a), the statistical value of the second ingredient information for the requested data amount is acquired. Therefore, after time t2, it is highly likely that more preferable sorting accuracy can be obtained by outputting the setting value of the sorting condition using both the first ingredient information and the second ingredient information. Therefore, the calculation unit 13 outputs the setting value of the sorting condition by the "second analysis method" between times t2 and t3.

[0039] At time t3 in FIG. 4(a), the value of the first ingredient information fluctuates greatly. Therefore, the calculation unit 13 can determine that time t3 is a "fluctuation point". For example, the calculation unit 13 may compare the current statistical value of the first ingredient information with the previous statistical value, and determine that the "fluctuation point" is present when the difference exceeds a threshold value. It is assumed that not only the first ingredient information but also the second ingredient information fluctuates greatly around time t3, which is the fluctuation point. Therefore, after time t3, if a statistical value including the second ingredient information acquired before time t3 is used, there is a high possibility that a preferable sorting accuracy cannot be obtained. Therefore, the calculation unit 13 outputs the setting value of the sorting condition by the "first analysis method" during the period from time t3 to t4.

[0040] At time t4 in FIG. 4(a), the statistical values ​​of the second ingredient information for the requested data amount are acquired. However, the statistical values ​​of the second ingredient information acquired at time t4 include the state of the mixture before the fluctuation point. Therefore, the statistical values ​​of the second ingredient information at time t4 may not accurately reflect the current state of the ingredients. Therefore, the calculation unit 13 continues to use the "first analysis method" between times t4 and t5.

[0041] At time t5 in FIG. 4(a), the statistical value of the second ingredient information is obtained. At least one second processing cycle has passed since time t3, which is the fluctuation point, at time t5. Therefore, the statistical value of the second ingredient information obtained at time t5 does not include the state of the mixture before the fluctuation point. In other words, the statistical value of the second ingredient information at time t4 is a low reliability data, and the statistical value of the second ingredient information at time t5 is a high reliability data. Therefore, after time t5, the calculation unit 13 outputs the setting value of the sorting condition by the "second analysis method".

[0042] Thereafter, the calculation unit 13 continues to detect the presence or absence of a fluctuation point based on the first ingredient information. If a fluctuation point is detected, the first analysis method is used until at least one second processing cycle has elapsed. After the fluctuation point, the second analysis method is used after one second processing cycle has elapsed. This allows the calculation unit 13 to output the setting values ​​of the sorting conditions with high accuracy using both the first ingredient information and the second ingredient information while excluding the use of the second ingredient information that contains a mixture of data before and after the fluctuation point.

[0043] In the second analysis method, if the second raw material information alone can output good and appropriate selection condition setting values, the first raw material information does not need to be used. In other words, in the second analysis method, at least the second raw material information needs to be used.

[0044] As described above, the sorting processing system 1 according to the present disclosure includes a sorting device 12 that sorts a mixture containing multiple types of objects by object type, a first detection unit 11 that acquires first raw material information on the mixture input to the sorting device 12, a second detection unit 21 that acquires second raw material information of a type different from the first raw material information on the mixture input to the sorting device 12, a calculation unit 13 having an analysis model that outputs a setting value on the sorting condition, and a control unit 14 that changes the sorting condition of the sorting device 12 based on the setting value output by the calculation unit 13. The calculation unit 13 processes the first raw material information every first processing cycle, and processes the second raw material information every second processing cycle that is longer than the first processing cycle. The calculation unit 13 switches between a first analysis method in which the first raw material information is input to an analysis model and a second analysis method in which at least the second raw material information is input to an analysis model and a setting value is output. According to this sorting processing system 1, in a configuration in which the statistical values ​​of the first ingredient information and the second ingredient information are obtained in a first processing cycle and a second processing cycle that are different from each other, it is possible to ensure sorting accuracy.

[0045] The calculation unit 13 may also detect a fluctuation point in the state of the mixture fed into the sorting device 12 based on the first raw material information processed at each first processing cycle, and output a set value using the first analysis method after the fluctuation point until at least the second processing cycle has elapsed. This configuration makes it possible to prevent the set value of the sorting condition from being determined using the second raw material information that includes data before the fluctuation point. Therefore, it is possible to prevent the sorting accuracy from decreasing at the fluctuation point.

[0046] The first raw material information may be a raw material composition ratio for each material in the plastic piece group P, and the first detection unit 11 may have a hyperspectral camera 11a that captures the plastic piece group P. In a configuration in which the hyperspectral camera 11a is used to detect the raw material composition ratio, the raw material composition ratio of 1000 flakes can be obtained per minute, for example. Therefore, the raw material composition ratio can be suitably used as the first raw material information for detecting a fluctuation point.

[0047] The technical scope of the present disclosure is not limited to the above-described embodiment, and various modifications can be made without departing from the spirit of the present disclosure.

[0048] For example, in the above embodiment, a group of plastic pieces P has been described as an example of a "mixture containing multiple types of objects" to be sorted by the sorting processing system 1. However, the sorting processing system 1 may also sort a mixture of objects other than plastic pieces. In this case as well, the present disclosure contributes to solving the problem of ensuring sorting accuracy in a configuration in which first raw material information and second raw material information are acquired in a first processing cycle and a second processing cycle that are different from each other.

[0049] In the above embodiment, it has been described that statistical values ​​(average values, etc.) of the first ingredient information, etc. are input to the analysis model. However, it is not essential to calculate statistical values. For example, the detection data by the first detection unit 11 or the second detection unit 21 may be directly input to the analysis model, and the setting values ​​of the sorting conditions may be output. In other words, "processing the first ingredient information for each first processing cycle" includes not only calculating statistical values, but also inputting the first ingredient information of the required data amount into the analysis model.

[0050] In the above embodiment, the raw material composition ratio is exemplified as the first raw material information, and the specific charge is exemplified as the second raw material information. As other examples, the first raw material information may be the input amount of the plastic piece group P, or the temperature and humidity in the environment of the sorting device 12. The second raw material information may be the moisture content in the flakes. Other types of first raw material information or second raw material information may be used. The calculation unit 13 may output the setting values ​​of the sorting conditions based on three or more pieces of raw material information.

[0051] That is, the amount of plastic piece group P input, the temperature and humidity in the environment of the sorting device 12, the moisture content in the flakes, etc. may be used as third raw material information different from the first raw material information and the second raw material information. In this case, in the first analysis method in Fig. 4(b), the first raw material information and the third raw material information may be input to the analysis model. In the second analysis method in Fig. 4(c), the first to third raw material information, or only the second raw material information and the third raw material information may be input to the analysis model.

[0052] Moreover, each function of the calculation unit 13, the control unit 14, etc. is realized by a processor such as a CPU (Central Processing Unit) executing a program stored in a program memory. Some or all of these functions may be realized by hardware such as an LSI (Large Scale Integration), an ASIC (Application Specific Integrated Circuit), or an FPGA (Field-Programmable Gate Array), or may be realized by software and hardware working together. The functions of the calculation unit 13 and the control unit 14 may be realized by the same hardware.

[0053] In the above embodiment, the case where plastic pieces are sorted by electrostatic sorting has been described. However, the sorting method is not limited, and may be, for example, specific gravity sorting or optical sorting. Specific gravity sorting is a sorting method that utilizes the fact that the specific gravity of each type of plastic piece is different. For example, when a group of plastic pieces is vibrated or floated on a medium, plastic pieces with a high specific gravity will descend and plastic pieces with a low specific gravity will rise.

[0054] Optical sorting is a sorting method that utilizes the fact that the reflectivity of light differs depending on the type of plastic piece. In optical sorting, a detection light is irradiated onto a group of plastic pieces, and the reflected light is detected. Light of various wavelengths, such as infrared rays or X-rays, can be used as the detection light. By detecting the spectrum of the reflected light or Raman scattered light, the plastic pieces can be distinguished by type. After distinguishing in this way, the plastic pieces may be sorted by air blowing, etc.

[0055] In addition, the above-described embodiments and modifications may be combined as appropriate. [Explanation of symbols]

[0056] REFERENCE SIGNS LIST 1...Sorting processing system 11...First detection unit 11a...Hyperspectral camera 12...Sorting device 13...Calculation unit 14...Control unit 21...Second detection unit P...Plastic pieces

Claims

1. A sorting system that sorts a mixture containing multiple types of objects using a sorting device, a first detection unit that acquires first raw material information regarding the mixture input into the sorting device; a second detection unit that acquires second raw material information of a type different from the first raw material information regarding the mixture input into the sorting device; a calculation unit that acquires the first raw material information from the first detection unit every first processing period, acquires the second raw material information from the second detection unit every second processing period that is longer than the first processing period, performs calculations, and determines whether or not there is a fluctuation point in the mixture that is input to the sorting device based on the first raw material information; a control unit that controls the sorting conditions of the sorting device using a set value based on the second raw material information after the calculation unit acquires the second raw material information from the second detection unit until it determines that the fluctuation point exists, and that controls the sorting conditions using a set value based on the first raw material information after the calculation unit determines that the fluctuation point exists until it acquires the second raw material information from the second detection unit. Sorting and processing system.

2. The calculation unit is provided with an analytical model that outputs a setting value related to the sorting conditions, and switches between a first analytical method in which the first raw material information is input to the analytical model and the setting value is output, and a second analytical method in which at least the second raw material information is input to the analytical model and the setting value is output, the calculation unit detects the fluctuation point of the state of the mixture input to the sorting device based on the first raw material information processed in each first processing cycle, and outputs the set value using the first analysis method after the fluctuation point until at least the second processing cycle has elapsed. The sorting system according to claim 1 .

3. The sorting device sorts the mixture by electrostatic sorting. The sorting system according to claim 1 or 2.

4. The mixture is a group of plastic pieces, and the type of object is a plastic material; The sorting system according to claim 1 or 2.

5. The first raw material information is a raw material composition ratio for each material in the group of plastic pieces, The sorting processing system according to claim 4 , wherein the first detection unit has a hyperspectral camera that captures images of the group of plastic pieces.

6. A sorting device that sorts a mixture containing multiple types of objects into individual object types; a first detection unit that acquires first raw material information regarding the mixture input into the sorting device; a second detection unit that acquires second raw material information of a type different from the first raw material information regarding the mixture input into the sorting device; a calculation unit including an analytical model that outputs setting values ​​related to the sorting conditions of the sorting device; a control unit that changes the sorting conditions of the sorting device based on the setting value output by the calculation unit, the calculation unit processes the first ingredient information for each first processing period, and processes the second ingredient information for each second processing period that is longer than the first processing period; the calculation unit switches between a first analysis method in which the first raw material information is input to the analysis model and the set value is output, and a second analysis method in which at least the second raw material information is input to the analysis model and the set value is output; the calculation unit detects a fluctuation point in the state of the mixture input to the sorting device based on the first raw material information processed in each first processing cycle, and outputs the set value using the first analysis method after the fluctuation point until at least the second processing cycle has elapsed. Sorting and processing system.

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