An apparatus and a method for sorting, particularly chopped, aluminum scrap by alloy groups are disclosed, in which the aluminum scrap is separated into fractions, fractions of the aluminum scrap are irradiated by at least one neutron source, the gamma radiation that the individual fraction emits due to this neutron irradiation is detected by at least one detector, and based on this, an energy spectrum associated with the respective fraction is generated, based on which energy spectrum a relative ratio of the weight proportions of at least two alloy elements of this fraction is determined, and based on this relative ratio, this fraction is allocated to its corresponding alloy group, and then the fractions are sorted by the alloy groups to which they have been allocated.

A sorting support apparatus is provided with: an input part that inputs a transmission image obtained by radiating an inspection target with electromagnetic waves; a storage part that stores a plurality of learning models optimized respectively for at least one article and being associated with an assumed usage condition; and a determination part that selects one of the learning models based on a specified usage condition and uses the learning model to determine whether or not the one or more articles is contained in the inspection target.

Techniques for processing ore include the steps of causing an imaging capture system to record a plurality of images of a stream of ore fragments en route from a first location in an ore processing facility to a second location in the ore processing facility; correlating the plurality of images of the stream of ore fragments with at least one or more characteristics of the ore fragments using a machine learning model that includes a plurality of ore parameter measurements associated with the one or more characteristics of the ore fragments; determining, based on the correlation, at least one of the one or more characteristics of the ore fragments; and generating, for display on a user computing device, data indicating the one or more characteristics of the ore fragments or data indicating an action or decision based on the one or more characteristics of the ore fragments.

Techniques for processing ore include the steps of causing an imaging capture system to record a plurality of images of a stream of ore fragments en route from a first location in an ore processing facility to a second location in the ore processing facility; correlating the plurality of images of the stream of ore fragments with at least one or more characteristics of the ore fragments using a machine learning model that includes a plurality of ore parameter measurements associated with the one or more characteristics of the ore fragments; determining, based on the correlation, at least one of the one or more characteristics of the ore fragments; and generating, for display on a user computing device, data indicating the one or more characteristics of the ore fragments or data indicating an action or decision based on the one or more characteristics of the ore fragments.

Techniques for processing ore include the steps of causing an imaging capture system to record a plurality of images of a stream of ore fragments en route from a first location in an ore processing facility to a second location in the ore processing facility; correlating the plurality of images of the stream of ore fragments with at least one or more characteristics of the ore fragments using a machine learning model that includes a plurality of ore parameter measurements associated with the one or more characteristics of the ore fragments; determining, based on the correlation, at least one of the one or more characteristics of the ore fragments; and generating, for display on a user computing device, data indicating the one or more characteristics of the ore fragments or data indicating an action or decision based on the one or more characteristics of the ore fragments.

Techniques for processing ore include the steps of causing an imaging capture system to record a plurality of images of a stream of ore fragments en route from a first location in an ore processing facility to a second location in the ore processing facility; correlating the plurality of images of the stream of ore fragments with at least one or more characteristics of the ore fragments using a machine learning model that includes a plurality of ore parameter measurements associated with the one or more characteristics of the ore fragments; determining, based on the correlation, at least one of the one or more characteristics of the ore fragments; and generating, for display on a user computing device, data indicating the one or more characteristics of the ore fragments or data indicating an action or decision based on the one or more characteristics of the ore fragments.

A method as well as an inspection device are provided for automatically checking the authenticity of objects, such as coins. The method includes carrying out an X-ray fluorescence analysis, XRFA, of an object which is to be checked, and carrying out a first comparison in which one or more properties of at least one fluorescence spectrum generated during the course of the XRFA are compared with an associated first body of reference information; carrying out a second analysis of the object on the basis of a corresponding second inspection method other than XRFA, as well as a second comparison in which an examination result obtained during the course of the second analysis is compared with an associated second body of reference information; and determining an analysis result relating to the authenticity of the object in dependence upon the results of the first comparison as well as the second comparison.

A method as well as an inspection device are provided for automatically checking the authenticity of objects, such as coins. The method includes carrying out an X-ray fluorescence analysis, XRFA, of an object which is to be checked, and carrying out a first comparison in which one or more properties of at least one fluorescence spectrum generated during the course of the XRFA are compared with an associated first body of reference information; carrying out a second analysis of the object on the basis of a corresponding second inspection method other than XRFA, as well as a second comparison in which an examination result obtained during the course of the second analysis is compared with an associated second body of reference information; and determining an analysis result relating to the authenticity of the object in dependence upon the results of the first comparison as well as the second comparison.

The ore intelligence sorting apparatus and method based on X-rays discernment includes a feeding unit with a toothed classifier, an X ray excitation unit with filter, a characteristic spectrum receiving unit with filter, a computer analysis and control unit with a central control unit, a spectral acquisition system, an industrial computer and an instruction output system, and a separator unit with a cylinder and a wear-resistant kick plate. The feeding unit is fed by a vibrating feeder and grading materials by a toothed classifier, and the measured ore is stimulated by the X ray excitation unit to produce a characteristic x ray spectra. The characteristic spectrum receiving unit receives the characteristic x ray spectrum which is then analyzed by the computer analysis and control unit, and a sorting instruction is output based on the analysis results. The invention is used for sorting magnetic or non-magnetic ores in a concentrator.

The ore intelligence sorting apparatus and method based on X-rays discernment includes a feeding unit with a toothed classifier, an X ray excitation unit with filter, a characteristic spectrum receiving unit with filter, a computer analysis and control unit with a central control unit, a spectral acquisition system, an industrial computer and an instruction output system, and a separator unit with a cylinder and a wear-resistant kick plate. The feeding unit is fed by a vibrating feeder and grading materials by a toothed classifier, and the measured ore is stimulated by the X ray excitation unit to produce a characteristic x ray spectra. The characteristic spectrum receiving unit receives the characteristic x ray spectrum which is then analyzed by the computer analysis and control unit, and a sorting instruction is output based on the analysis results. The invention is used for sorting magnetic or non-magnetic ores in a concentrator.