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Dr. Ramírez-Arias, Guillermo
Nombre de publicación
Dr. Ramírez-Arias, Guillermo
Nombre completo
Ramírez Arias, Guillermo Esteban
Facultad
Email
guillermoramirez@ucsc.cl
ORCID
2 results
Research Outputs
Now showing 1 - 2 of 2
- PublicationIdentification of impact frequency for down-the-hole drills using motor current signature analysis(Applied Sciences, 2023)
;Brito, Diego ;Gómez, René ;Carvajal, Gonzalo ;Reyes-Chamorro, LorenzoIn rotary-percussion drilling, the impact frequency is a crucial variable that is closely linked to operational factors that determine the efficacy of the drilling process, such as the rate of penetration, bit wear, and rock mass characteristics. Typical identification methods rely on complex simulation models or the analysis of different sensor signals installed on specially adapted setups, which are difficult to be implemented in the field. This paper presents a novel study where the impact frequency is identified by motor current signature analysis (MCSA) applied to an induction motor driving a DTH drilling setup. The analysis of the case study begins with the definition of characteristic drilling stages where the pressure and sound signals allow the detection of an impact frequency of 14.10 Hz, which is then used as a reference to validate three MCSA identification approaches. As a result of the analysis, the envelope approach is the most robust for nearly real-time implementations considering its simplicity and range of coverage. Experimental results provide evidence about the feasibility of the proposed MCSA methods to be integrated into Measurement-While-Drilling (MWD) systems to improve drilling condition monitoring and rock mass characterization. - PublicationElectro-Mechanical modeling and evaluation of electric load haul dump based on field measurements(Energies, 2023)
;Freire, Gabriel; ;Gómez, René ;Skrzypkowski, KrzysztofZagórski, KrzysztofIn underground mining, conventional loader equipment uses diesel as a power source, implying different drawbacks, such as combustion gases, low visibility, worker’s health problems, and high ventilation requirements. Thus, hybrid and electric loaders are being developed by the main industry suppliers who prefer clean technology. In this study, we analyzed the performance of an electro-mechanical powertrain through a dynamic model of underground-loader equipment using field data. This electric LHD model was compared to a diesel loader under the same operational conditions. For the case study, the results showed that the proposed electro-mechanical model, considering 14 tons of capacity, consumed 86.8 kWh, representing 60.5% less energy than the diesel loader with similar speed and torque characteristics. Thus, the proposed methodology is a valuable tool for operators, process engineers, and decision-makers, allowing an energy-efficiency evaluation for electric LHD adoption, based on the current operational data available for conventional equipment.