Sensing and data fusion opportunities for raw material characterisation in mining: Technology and data-driven approach

The rising demands for mined products lead to the extraction of materials in geologically complex regions. This calls for mining process changes and interventions driven by technology and advanced data analytics. The dynamic development of state-of-the-art sensor technologies and their potential use in mining is projected to significantly reduce...

Image and point data fusion for enhanced discrimination of ore and waste in mining

Sensor technologies provide relevant information on the key geological attributes in mining. The integration of data from multiple sources is advantageous in making use of the synergy among the outputs for the enhanced characterisation of materials. Sensors produce various types of data. Thus, the fusion of these data requires innovative data...

Fusion of Mid-Wave Infrared and Long-Wave Infrared Reflectance Spectra for Quantitative Analysis of Minerals

Accurate quantitative mineralogical data has significant implications in mining operations. However, quantitative analysis of minerals is challenging for most of the sensor outputs. Thus, it requires advances in data analytics. In this work, data fusion approaches for integrating datasets pertaining to the mid-wave infrared (MWIR) and long-wave...

Data Fusion for the Prediction of Elemental Concentrations in Polymetallic Sulphide Ore Using Mid-Wave Infrared and Long-Wave Infrared Reflectance Data

The increasing availability of complex multivariate data yielded by sensor technologies permits qualitative and quantitative data analysis for material characterization. Multivariate data are hard to understand by visual inspection and intuition. Thus, data-driven models are required to derive study-specific insights from large datasets. In the...

Evaluation of sensor technologies for on-line raw material characterization in “Reiche Zeche” underground mine - outcomes of RTM implementation

The increasing advances in sensor technology have resulted in greater availability of sensor data for a wide range of applications. One such application is raw material characterization in mining operations. Sensor technologies operate over certain range of the electromagnetic spectrum and provide information on several aspects of material...

Real -Time Mining: Sensors for materials characterization

Sensors are being used as laboratory and in-situ techniques for characterization and definition of raw material properties. However, application of sensor technologies for underground mining resource extraction is very limited and highly dependent on the geological and operational environment. In our study the potential of RGB imaging, Fourier...

Chemometric Analysis of Mid-Wave Infrared Spectral Reflectance Data for Sulphide Ore Discrimination

Despite significant recent advancements in the sensor technologies, the use of sensors for raw material characterization in the mining industry remains limited. The aim of the present study was to assess the utility of applying the mid-wave infrared (MWIR) reflectance data acquired by the use of a handheld Fourier-transform infrared...

Automation in sensing and raw material characterization - A conceptual framework

The use of sensor technologies for material characterization is rapidly growing and innovative advancement is observed. However, the use of sensor combinations for a raw material characterization in mining is very limited and automation of the material identification process using a combined sensor signal is not defined. Potential sensor...

The use of RGB Imaging and FTIR Sensors for Mineral mapping in the Reiche Zeche underground test mine, Freiberg

The application of sensor technologies for raw material characterization is rapidly growing, and innovative advancement of the technologies is observed. Sensors are being used as laboratory and in-situ techniques for characterization and definition of raw material proper-ties. However, application of sensor technologies for underground mining...