Performance evaluation of optical sorting in mineral processing – A case study with quartz, magnesite, hematite, lignite, copper and gold ores

Gülcan, Ergin; Gülsoy, Özcan Y.

doi:10.1016/j.minpro.2017.11.007

Cited by 26 publications

(15 citation statements)

References 10 publications

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“…Whenever this deadline is missed, these objects falsely remain in the accepted material. Besides monochrome and color cameras [3], [12], examples include X-ray transmission [13]- [16], near-infrared and hyperspectral cameras [2], [17]- [19] as well as systems that combine different sensors [8], [16], [20]. An example for non-imaging sensors is the application of microphones, for instance to characterize materials based on impact resonant acoustic emissions [8].…”

Section: A Functional Principlementioning

confidence: 99%

“…SOCs are intended to support the choice of an operating point based on yield and quality factors and predict the sorting quality. In [3], the authors adapt the conventional approach of confusion matrices, which are typically used to evaluate a classifier, to sensor-based sorting. This enables the usage of well-known figures of merit such as accuracy, specificity and sensitivity.…”

Section: Related Workmentioning

confidence: 99%

“…For instance, in the field of mineral processing, the efficient extraction and recovery of raw materials is crucial due to limited existing reserves. Examples include the sorting of porphyry copper [2], quartz, magnesite and gold ores [3], [4]. In food processing, products, e.g., dried vegetables, fruits [5] and nuts [6], often need to be cleaned from foreign, potentially dangerous objects as well as low-quality and damaged entities.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Experimental Evaluation of a Novel Sensor-Based Sorting Approach Featuring Predictive Real-Time Multiobject Tracking

Maier

Pfaff

Pieper

et al. 2021

IEEE Trans. Ind. Electron.

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Sensor-based sorting is a machine vision application that has found industrial application in various fields. An accept-or-reject task is executed by separating a material stream into two fractions. Current systems use line-scanning sensors, which is convenient as the material is perceived during transportation. However, line-scanning sensors yield a single observation of each object and no information about their movement. Due to a delay between localization and separation, assumptions regarding the location and point in time for separation need to be made based on the prior localization. Hence, it is necessary to ensure that all objects are transported at uniform velocities. This is often a complex and costly solution. In this paper, we propose a new method for reliably separating particles at non-uniform velocities. The problem is transferred from a mechanical to an algorithmic level. Our novel advanced image processing approach includes equipping the sorter with an area-scan camera in combination with a real-time multiobject tracking system, which enables predictions of the location of individual objects for separation. For the experimental validation of our approach, we present a modular sorting system, which allows comparing sorting results using a line-scan and area-scan camera. Results show that our approach performs reliable separation and hence increases sorting efficiency. Index Terms-Automated visual inspection, machine vision, real-time multiobject tracking, sensor-based sorting.

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Section: A Functional Principlementioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Experimental Evaluation of a Novel Sensor-Based Sorting Approach Featuring Predictive Real-Time Multiobject Tracking

Maier

Pfaff

Pieper

et al. 2021

IEEE Trans. Ind. Electron.

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“…Hence, the application of a correlation coefficient derived from these results would be sufficient in terms of an accurate representation of the Fe2O3 grades. Gulcan and Gulsoy (2017) have pointed out that optical sorting, which is a method based on DIP, of quartz and magnesite samples were resulted in high sorting efficiencies due to fact that both samples having high color contrast among their particles. On the other hand, it was also stated that the same separation method arose some challenges for the samples that have moderate color-contrast (lignite and hematite) and low color contrast (copper and gold).…”

Section: Comparison Of Dip and Icp Assay Valuesmentioning

confidence: 99%

Digital image processing (DIP) application on the evaluation of iron-rich heavy mineral concentrates produced from river sand using a sequential mineral processing approach

Terzi¹,

Kurşun²,

Çınar³

et al. 2021

Physicochem. Probl. Miner. Process.

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In this study, the iron-rich heavy mineral concentrate production from river sand as a byproduct of an alternative resource by gravity, magnetic separation, and flotation methods were investigated in detail. For the physical separation of the sample and increasing the Fe2O3 content, a shaking table and a wet high-intensity magnetic separator were used, respectively. The gravity and magnetic separation experiments included rougher, cleaner, and scavenger circuits. In the flotation experiments, cationic flotation with ethylenediamine under acidic conditions, and anionic flotation with sodium oleate under alkaline conditions were performed. The iron and silica content of the products obtained were determined by digital image processing (DIP) methods and compared with the classical analytical procedures. Finally, a flow chart was proposed for the processing of the ore according to the optimum enrichment parameters were determined from the experiments. The results obtained in this study show that it is possible to produce an iron-rich heavy mineral concentrate with Fe2O3 grade and recovery rate of 79.13% and 57.81%, respectively, in addition to a potential feed for the production of quartz sand and feldspar concentrates.

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“…The method and design of the apparatus for sorting small sized workpieces from minerals and semiprecious stones proposed can reduce the amount of waste in the process of further mechanical processing of minerals for the purpose of manufacturing jewelry [22], [23]. The proposed method for sorting minerals is aimed at increasing the volume of finished jewelry from one mineral.…”

Section: Solution Of the Problem Under Considerationmentioning

confidence: 99%

Intelligent machine for sorting semi-precious minerals

Polishchuk

Tkach

Parkhomey

et al. 2021

IJEECS

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This paper proposes is devoted to solving the problem of sorting workpieces from minerals and semi-precious stones that are used in jewelry production. Intensive development of production leads to a reduction of natural resources, including semi-precious minerals. Therefore, the task of saving the use of minerals is relevant. The solution is based on the idea a new method for sorting semi-precious minerals is proposed, as well as the design of an intelligent installation for implementing this method. An increase in the accuracy of sorting semiprecious minerals has been achieved through the use of charge-coupled device (CCD) matrices, which automatically determine the volume of each mineral in 3D space. From the simulation work, it was found in comparison with manual sorting, the proposed method has reduced the amount of waste in the manufacture of jewelry by 15% ... 20%. Experimental studies were carried out using the example of such a semiprecious mineral as amber. The cost of raw amber in the amount of one kilogram on the modern market is in the range of 1200…2200 US dollars. The result confirms that the method is superior to the alternative method, with the achieved average waste saving of 20%, the proposed sorting technology makes it possible to obtain a profit of 240...440 US dollars per kilogram of amber. Ultimately, these solutions can improve the efficiency of jewelry production.

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Performance evaluation of optical sorting in mineral processing – A case study with quartz, magnesite, hematite, lignite, copper and gold ores

Cited by 26 publications

References 10 publications

Experimental Evaluation of a Novel Sensor-Based Sorting Approach Featuring Predictive Real-Time Multiobject Tracking

Experimental Evaluation of a Novel Sensor-Based Sorting Approach Featuring Predictive Real-Time Multiobject Tracking

Digital image processing (DIP) application on the evaluation of iron-rich heavy mineral concentrates produced from river sand using a sequential mineral processing approach

Intelligent machine for sorting semi-precious minerals

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