Mining Project: Developing a Real-Time Ground Stability Informatics System
To enable better detection of ground control hazards for underground mine workers.
According to Mine Safety and Health Administration (MSHA) accident illness, and injury data analyzed by NIOSH researchers, falls of ground made up 8% of the non-fatal days lost (NFDL) injuries and 29% of the fatalities at underground metal/nonmetal mines between 2011 and 2016, and made up 13% of NFDL injuries for the mining industry as a whole during the same time frame. While ground falls may not be as common as other mining incidents, they are more likely to be fatal and have the potential to cause widespread damage to the mine workings. Additionally, the use of automation is growing in the mining industry, with smart mining technology generating a global revenue of $6.80 billion in 2016 and projected to reach $16.25 billion by 2025.
This increasing prevalence of automated and tele-operated equipment in underground mining environments could result in less consistent monitoring of ground conditions because of the reduced presence of miners in the mine workings. Historically, experienced miners have been critical to assessing ground control issues and to making immediate changes to support requirements and mining if observations warrant these actions. Without the continual presence of miners in these areas, ground monitoring practices must change and this information must be collected and presented in new ways, in particular because workers will still need to enter the mine to perform tasks that are not automated.
Further, if a ground failure were to trap automated equipment it would require risk-prone rescue efforts by mine workers or mine rescue personnel. Advances in sensor technology, wireless communications, data analytics, and data visualization technologies are available and are used in other industries. The mining industry would benefit from the application of these advances to monitor ground stability both where automation is implemented and where traditional mining equipment and methods are used. The development of a system to analyze ground stability and provide real-time feedback to mine workers would address the above issues by providing a means to remotely monitor stability in these areas.
To address these issues, this project has three research aims:
- conduct a gap analysis of ground stability data, analysis, and visualization technologies needed to make timely and actionable decisions about ground stability in underground metal mines;
- develop the framework for a ground stability informatics system (GSIS) to enable real-time ground stability analysis and visualization; and
- test a prototype GSIS in order to verify that it is able to correctly identify hazardous situations from case study data and demonstrate its effectiveness in a mine environment.
To accomplish these aims, the research team will evaluate the mining industry’s needs and review existing technologies for underground ground stability monitoring and analysis through literature reviews and discussions with collaborators and other industry experts. A goal-directed task analysis will be conducted to assess the requirements for the user interface for a GSIS. The framework for this system will be developed based on the results of the gap analysis, and researchers will explore options for advanced data analytics such as statistical learning and three-dimensional visualization.
The developed system will undergo both laboratory and field testing. In the lab, researchers will verify that the system performs adequately using mock data, and potential system users will evaluate the user interface. In field testing, the system will be installed at a cooperating mine site and its performance will be evaluated using observations from mine workers and the existing ground stability assessment methods.
Ultimately, this project research will fill technology gaps related to ground stability monitoring by developing a system to integrate geomechanical data into an analytics and visualization package that can highlight the most relevant ground stability information to mining operators in real time. Technology developed from this research would extend to all underground metal mines applying varying degrees of automation, as well as traditional mining systems. Additionally, many aspects of this research may be applicable to the broader mining industry, such as underground stone or coal.