Classifying of materials with contaminants
A material sorting system sorts materials utilizing a vision system that implements a machine learning system in order to identify or classify each of the materials, which are then sorted into separate groups based on such an identification or classification. The material sorting system can sort material pieces containing contaminants, such as copper from steel.
1 . A system for handling a first mixture of material pieces, the system comprising:
a camera configured to capture visual images of the first mixture of material pieces to produce image data, wherein the image data captures one or more visually observed characteristics of each of the first mixture of material pieces; and
a data processing system comprising an artificial intelligence (“AI”) system configured to classify one or more of the material pieces as containing a contaminant based on the one or more visually observed characteristics that represent visually discernible characteristics indicative of a chemical composition possessed by materials containing a contaminant.
2 . The system as recited in claim 1 , wherein the first mixture of material pieces is composed of plastics, and wherein the contaminant is a specified additive.
3 . The system as recited in claim 1 , wherein the contaminant is embedded within the classified material pieces.
4 . The system as recited in claim 3 , wherein the first mixture of material pieces is composed of ferrous metals, and wherein the contaminant is copper.
5 . The system as recited in claim 1 , wherein the classifying of one or more of the material pieces as containing a contaminant is based on a knowledge base containing a previously generated library of observed characteristics captured from samples of material pieces containing the contaminant.
6 . The system as recited in claim 1 , further comprising:
a conveyor system configured to convey the first mixture of material pieces past the camera; and
a sorter configured to sort the one or more classified material pieces from the first mixture of material pieces as a function of the classifying of the one or more of the material pieces as containing a contaminant.
7 . The system as recited in claim 6 , wherein the first mixture of material pieces is composed of ferrous metals, and wherein the contaminant is copper, wherein the sorting by the sorter of the classified material pieces from the first mixture of material pieces produces a second mixture of material pieces that comprises the first mixture of material pieces minus the classified material pieces, wherein one or more parameters within the AI system are configured to classify one or more of the material pieces so that the second mixture of material pieces contains an aggregate amount of copper of less than 1 wt %.
8 . The system as recited in claim 6 , wherein the first mixture of material pieces is composed of ferrous metals, and wherein the contaminant is copper, wherein the sorting by the sorter of the classified material pieces from the first mixture of material pieces produces a second mixture of material pieces that comprises the first mixture of material pieces minus the classified material pieces, wherein one or more parameters within the AI system are configured to classify one or more of the material pieces so that the second mixture of material pieces contains an aggregate amount of copper of less than 0.05 wt %.
9 . A method for handling a first mixture of materials, the method comprising:
capturing a characteristic of the first mixture of materials with a camera configured to capture visual images of the materials; and
assigning with an AI system a classification to certain ones of the first mixture of materials as containing a contaminant based on the captured characteristic of the first mixture of materials, wherein the captured characteristic represents a visually discernible characteristic that is indicative of a chemical composition possessed by materials containing a contaminant.
10 . The method as recited in claim 9 , wherein the classification is based on a knowledge base containing a previously generated library of one or more observed characteristics captured from a set of samples of materials containing the contaminant.
11 . The method as recited in claim 9 , wherein the first mixture of materials is composed of ferrous metals, and wherein the contaminant is copper.
12 . The method as recited in claim 11 , further comprising sorting the certain ones of the first mixture of materials from the first mixture of materials as a function of the classification, wherein the sorting produces a second mixture of materials that comprises the first mixture of materials minus the sorted certain ones of the first mixture of materials.
13 . The method as recited in claim 12 , wherein the second mixture of materials contains an aggregate amount of copper of less than 1 wt %.
14 . The method as recited in claim 12 , wherein the second mixture of materials contains an aggregate amount of copper of less than 0.05 wt %.
15 . The method as recited in claim 9 , wherein the first mixture of materials is composed of plastics, and wherein the contaminant is a specified additive.
16 . A computer program product stored on a computer readable storage medium, which when executed by a data processing system, performs a process comprising:
assigning with an AI system a classification to certain ones of a mixture of material pieces as containing a contaminant based on one or more characteristics embodied in visual images of the mixture of material pieces captured with a camera, wherein the one or more characteristics of the certain ones of the mixture of material pieces classified as containing the contaminant represent visually discernible characteristics that are indicative of a chemical composition possessed by materials containing a contaminant; and
sending instructions to a sorting device to sort the certain ones of the mixture of material pieces from the mixture, wherein the sorting is performed as a function of the classification.
17 . The computer program product as recited in claim 16 , wherein the classification is based on a knowledge base containing a previously generated library of one or more observed characteristics captured from a set of samples of material pieces containing the contaminant.
18 . The computer program product as recited in claim 16 , wherein the mixture of material pieces is composed of plastics, and wherein the contaminant is a specified additive.
19 . The computer program product as recited in claim 16 , wherein the mixture of material pieces is composed of ferrous metal scrap pieces, and wherein the contaminant is copper embedded within one or more of the ferrous metal scrap pieces.
20 . The computer program product as recited in claim 19 , wherein one or more parameters within the AI system are configured to classify the material pieces so that the certain ones of the mixture of material pieces contains an aggregate amount of copper of less than 1 wt %.
21 . The computer program product as recited in claim 19 , wherein one or more parameters within the AI system are configured to classify the material pieces so that the certain ones of the mixture of material pieces contains an aggregate amount of copper of less than 0.05 wt %.
22 . A system for handling a first mixture of material pieces composed of ferrous metals, the system comprising:
a sensor configured to capture one or more characteristics of the first mixture of material pieces composed of ferrous metals;
a data processing system comprising an artificial intelligence (“AI”) system configured to classify one or more of the material pieces composed of ferrous metals as containing a tramp element based on the one or more captured characteristics of the first mixture of material pieces composed of ferrous metals;
a conveyor system configured to convey the first mixture past the sensor; and
a sorter configured to sort the one or more classified material pieces from the first mixture as a function of the classifying of the one or more of the material pieces composed of ferrous metals as containing a tramp element, wherein the sorting by the sorter of the classified material pieces from the first mixture produces a second mixture of material pieces that comprises the first mixture minus the classified material pieces, wherein the second mixture of material pieces contains an aggregate amount of the tramp element of less than 0.05 wt %.