Abstract: A material sorting system sorts materials utilizing an x-ray fluorescence and/or 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 determining that the materials are composed of either wrought aluminum, extruded aluminum, or cast aluminum. The system is capable of sorting between cast aluminum alloys and also between wrought aluminum alloys.

Abstract: Systems and methods for classifying materials utilizing one or more sensor systems, which may implement a machine learning system in order to identify or classify each of the materials, which may then be sorted into separate groups based on such an identification or classification. The machine learning system may utilize a neural network, and be previously trained to recognize and classify certain types of materials.

Abstract: Systems and methods for classifying and sorting of plastic materials utilizing a vision system and one or more sensor systems, which may implement a machine learning system in order to identify or classify each of the materials, which may then be sorted into separate groups based on such an identification or classification.

Abstract: A sorting system conveys a heterogeneous mixture of material pieces past an XRF system and a vision system. A classification of a material piece is changed to a high copper content aluminum alloy when the XRF system classifies the material piece as a low copper content aluminum alloy and the vision system determines that the material piece is a thin strip material piece. The reclassified material piece is then sorted accordingly.

Abstract: When x-ray fluorescence (“XRF”) spectroscopy is utilized to classify materials transported on a moving conveyor belt, there is the possibility of the x-ray beam only partially irradiating the material piece, which can result in the capture of an inaccurate XRF spectrum needed to classify the material piece. This can lead to an improper (erroneous) classification and resultant sortation of material pieces (e.g., aluminum alloys). In a material handling system, the area of the intersections between the x-ray beam spots from an x-ray fluorescence system and the material pieces are measured and correspondingly used to correct the measured XRF spectrum associated with each material piece. The material pieces can then be sorted according to the corrected XRF spectrum.

Abstract: A material sorting system sorts materials utilizing an x-ray fluorescence and/or 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 determining that the materials are composed of either wrought aluminum, extruded aluminum, or cast aluminum. The system is capable of sorting between cast aluminum alloys and also between wrought aluminum alloys.

Abstract: A mobile sorter for sorting materials, such as from a waste landfill. The mobile sorter includes a mobile platform with a mechanism configured to transport the mobile platform over ground. A sorting system mounted onto the mobile platform is configured to identify a specific type of material piece from different types of material pieces and sort that specific type of material piece from the different types of material pieces as the different types of material pieces are conveyed via a first conveyor system through the sorting system from a heap of the different types of material pieces. An apparatus is configured to collect the different types of material pieces from the heap and feed the different types of material pieces onto the first conveyor system.

Abstract: A portable materials analyzer is implemented in a small form factor. A sample of material pieces are retrieved from a larger container. The sample of material pieces are then analyzed by the analyzer using x-ray fluorescence, laser induced breakdown spectroscopy, a vision system with artificial intelligence, etc. The number of the material pieces within the sample is a substantially small percentage of a total number of the material scrap pieces within the container. The analyzer then determines whether the classification of the material pieces within the sample corresponds to an expected classification of the entirety of material pieces within the container.

Abstract: A material handling system sorts materials utilizing a vision system of multiple vision devices configured with single board computers that each implement an artificial intelligence system in order to identify or classify materials, which are then sorted into separate groups based on such an identification or classification by sorting devices that are each coupled to one of the vision devices.

Abstract: An apparatus for classifying materials utilizing a vision system, which may implement an artificial intelligence system in order to identify or classify each of the materials, which may then be separated from a heap in a scrap yard into separate groups, such as other heaps, based on such an identification or classification. The artificial intelligence system may utilize a neural network, and be previously trained to recognize and classify certain types of materials.

Abstract: A system classifies materials utilizing a vision system that implements an artificial intelligence system in order to identify or classify and then remove automotive airbag modules from a scrap stream, which may have been produced from a shredding of end-of-life vehicles. The sorting process may be designed so that live airbag modules are not activated, which may cause damage to equipment or persons.

Abstract: 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.

Abstract: 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 determining that the materials are composed of either wrought aluminum, extruded aluminum, or cast aluminum.

Abstract: Systems and methods for classifying and sorting materials in order to produce a collection of materials that are composed of a particular chemical composition in the aggregate. The system may utilize a vision system and one or more sensor systems, which may implement a machine learning system in order to identify or classify each of the materials. The sorting is then performed as a function of the classifications.

Abstract: A material sorting system sorts materials utilizing multiple stages of classification and sorting, including a vision system that implements a machine learning system in order to identify or classify each of the materials, and Laser Induced Breakdown Spectroscopy to perform a subsequent classification and sorting of the remaining materials.

Abstract: Systems and methods for classifying and sorting of plastic materials utilizing a vision system and one or more sensor systems, which may implement a machine learning system in order to identify or classify each of the materials, which may then be sorted into separate groups based on such an identification or classification.

Abstract: A material sorting system sorts materials utilizing multiple stages of classification and sorting, including a vision system that implements a machine learning system in order to identify or classify each of the materials, and Laser Induced Breakdown Spectroscopy to perform a subsequent classification and sorting of the remaining materials.

Abstract: A system classifies materials utilizing a vision system that implements a machine learning system, such as a neural network, in order to identify or classify each of the materials as either a monetary coin or not a monetary coin, which may then be sorted into separate groups based on such an identification or classification. Such a system can sort monetary coins from other forms of scrap, which may have been produced from a shredding of end of life vehicles.

Abstract: A mercury emissions monitor includes a mercury sensor tape configured to be fed in a reel-to-reel manner between first and second tape reels, wherein the mercury sensor tape includes a thin metallic film configured to form an amalgam with detected mercury. A mercury collection unit is configured to receive into a chamber a sample of a gas containing mercury, wherein the mercury collection unit is further configured to permit passage of portions of the mercury sensor tape through the chamber containing the gas sample so that the amalgam is formed with the thin metallic film. A mercury analysis unit includes a total reflection x-ray fluorescence (“TXRF”) system configured to perform a TXRF analysis of the amalgam, wherein the mercury analysis unit is configured to permit passage of the mercury sensor tape within a proximity of an XRF detector of the TXRF system.

Abstract: Systems and methods for classifying materials utilizing one or more sensor systems, which may implement a machine learning system in order to identify or classify each of the materials, which may then be sorted into separate groups based on such an identification or classification. The machine learning system may utilize a neural network, and be previously trained to recognize and classify certain types of materials.