A comprehensive review of froth surface monitoring as an aid for grade and recovery prediction of flotation process. Part B: Texture and dynamic features

ABSTRACT

In the last few decades, many studies have been performed with the main hope of utilizing imaging methods so as to detect static (bubble size and shape, color, texture) and dynamic (velocity and stability) features of froth that involve crucial information about the process state in order to assess and monitor the performance of flotation process. Although several types of flotation automated control system problems are being successfully solved using the various techniques of features extraction from froth images, there are still a number of unresolved subjects and obstacles. Hence, a suitable review of these methods is needed. After reviewing the technical aspects of froth images structural features in part 1 of this two-part review paper, this work provides an overview of several different approaches for the sake of analyzing and classifying froth image texture and dynamic features. Finally, we conclude our review by linking concentrate grade and recovery with the froth image features described in this two-part paper. In the close future, it is expected with ever-growing application needs and research progress, image analysis systems are becoming even more effective solutions for monitoring and controlling flotation performance. This review provides a platform for future initiatives and potential developments in this area.

KEYWORDS:

• Froth flotation
• Image analysis
• Texture and dynamic features
• Grade
• recovery

Additional information

Notes on contributors

Fardis Nakhaei

Fardis Nakhaei was born in Iran, in 1986. He received the PhD degree of mineral processing in Department of Mining & Metallurgical Engineering, Amirkabir University of Technology, Iran in 2018. His research activity is on the modelling and control for the mineral processing processes.

Mehdi Irannajad

Mehdi Irannajad is an associate professor in Department of Mining & Metallurgical Engineering, Amirkabir University of Technology, Iran. His research interests are the mineral processing and process mineralogy.

Sima Mohammadnejad

Sima Mohammadnejad received the PhD degree of mineral processing from the University of Melbourne, Australia, in 2014. She is an assistant professor in Tarbiat Modararres University, Iran. She has extensive experience in the characterization and processing of ores, combining her knowledge and expertise in both mineralogy and processing.