Toward the Optimization of Mining Operations Using an Automatic Unmineable Inclusions Detection System for Bucket Wheel Excavator Collision Prevention: A Synthetic Study

被引：1

作者：

Kritikakis, George ^{[1
]}

Galetakis, Michael ^{[1
]}

Vafidis, Antonios ^{[1
]}

Apostolopoulos, George ^{[2
]}

Michalakopoulos, Theodore ^{[2
]}

Triantafyllou, Miltiades ^{[3
]}

Roumpos, Christos ^{[3
]}

Pavloudakis, Francis ^{[4
]}

Deligiorgis, Basileios ^{[1
]}

Economou, Nikos ^{[1
]}

Andronikidis, Nikos ^{[1
]}

机构：

[1] Tech Univ Crete Campus, Sch Mineral Resources Engn, Khania 73100, Greece

[2] Natl Tech Univ Athens, Sch Min & Met Engn, Iroon Polytech 9 Str,Zografou Campus, Athens 15773, Greece

[3] Publ Power Corp, Min Engn & Closure Planning Dept, Chalkokondili 29 Str, Athens 10432, Greece

[4] Univ Western Macedonia, Sch Engn, Dept Mineral Resources Engn, Kozani 50100, Greece

来源：

SUSTAINABILITY | 2023年 / 15卷 / 17期

关键词：

bucket wheel excavator; unmineable inclusions detection; electromagnetic inspection; fuzzy inference system; collision prevention;

D O I：

10.3390/su151713097

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

This work introduces a methodology for the automatic unmineable inclusions detection and Bucket Wheel Excavator (BWE) collision prevention, using electromagnetic (EM) inspection and a fuzzy inference system. EM data are collected continuously ahead from the bucket wheel of a BWE and subjected to processing. Two distinct methodologies for data processing were developed and integrated into the MATLAB programming environment. The first approach, named "Simple Mode", utilizes statistical process control to generate real-time alerts in the event of a potential collision involving the excavator's bucket and hard rock inclusions. The advanced processing flow ("Advanced Mode") requires accurate instrument positioning and data from successive EM scans. It incorporates techniques of local resistivity maxima detection (Position Prominence Index) as well as Neural Network-based Pattern Recognition (NNPR). A decision support process based on a Fuzzy Inference System (FIS) has been developed to assist BWE operators in avoiding collision when digging hard rock inclusions. The proposed methodology was extensively tested using synthetic EM data. Limited real data, acquired with a CMD2 (GF Instruments) EM instrument equipped with GPS, were used to control its efficiency. Increased accuracy in the automatic detection of unmineable inclusions was observed using the Advanced Mode. On the other hand, the Simple Mode processing technique offers the advantage of being independent of instrument positioning as well as it provides real-time inspection of the excavated mine slope. This work introduces a methodology for hard rock inclusion detection and can contribute to the optimization of mine operations by improving resource efficiency, safety, cost savings, and environmental sustainability.

引用

页数：20