Mining Project: Developing a Real-Time Ground Stability Informatics System

Keywords: Ground control
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Principal Investigator
Start Date 10/1/2018
End Date 9/30/2020

To identify needs for enabling better detection of ground control hazards in underground metal mines.

Topic Area

Research Summary

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.

In an effort to adapt to increasingly challenging mining conditions, some mines are beginning to explore the use of automated mining equipment, 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 themselves have been the monitoring systems in underground mines, relying on sensory input to assess and identify ground control issues. Miners use three senses for monitoring ground stability conditions:

  • vision—conducting inspections of the rock mass and support system for damage, mapping structures, and identifying loose/sloughed material or convergence,
  • hearing—listening for changes in how the rock mass cracks and pops in response to mining, and
  • touch—taking samples, observing how equipment interacts with the rock, and sounding it with a scaling bar or hammer to gauge its competence.

Without the continual presence of miners in in active headings, 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. Furthermore, if a ground failure were to trap automated equipment it would require risk-prone rescue efforts by mine workers that would be further complicated by not having a good understanding of ground conditions.

New technology to provide real-time information about the underground environment could be used as a way to replace this feedback. 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 had two research aims: 

  • to evaluate current technology for ground stability monitoring in underground metal mining, particularly as it applies to monitoring in environments that are unfrequented by mine workers, and
  • to identify any gaps that NIOSH should/could address in the future relating to geotechnical monitoring in underground environments.

To accomplish these aims, the research team evaluated the state of ground control monitoring in underground U.S. metal mines and existing technologies through literature reviews and discussions with collaborators and other industry experts. The purpose of these reviews and discussions was to explore how underground metal mines in the U.S. make use of ground stability data, with a goal of understanding what data ground control engineers are collecting, how the data are collected, stored, and analyzed, and how the resulting information is used to influence ground-control-related decisions.

The reviews conducted during this project resulted in the identification of several barriers to adopting ground stability monitoring technology in underground mining, including:

  • understaffed ground control departments,
  • poor awareness of existing tools and technologies,
  • justifying the investment in modern technology,
  • limited interoperability between systems, and
  • inconsistent data management practices.

Additionally, researchers determined several components and considerations that should be considered in implementing a holistic remote ground control monitoring strategy, including:

  • remote imaging of the mining face for geotechnical mapping, rock mass characterization, and hazard mapping;
  • ground support performance monitoring instrumentation and a system for integrating data from various aspects of the ground support process (installation parameters, amounts and types of support, conditions of support, etc.);
  • seismic monitoring;
  • an underground information infrastructure capable of transmitting data from wireless instrumentation;
  • data management practices that support version-controlling and a single source of truth for all geotechnical data at a mine site;
  • open data standards to facilitate information sharing between different geotechnical systems; and
  • the use of platforms that allow for the integration, analysis, and visualization of geotechnical data in a holistic manner.

Some of these components are mature, while others will require additional research and development. Additionally, not all of these components will be applicable to all mining operations and depend on factors such as mining method, geotechnical challenges, and budgets specific to mine sites.

The identification of these gaps and needs will enable researchers to determine ground control research areas that could be the focus of future research to facilitate a more widespread adoption of remote ground stability monitoring solutions. The outcomes from this research apply to all underground metal mines applying varying degrees of automation, though aspects of this work can be extended to traditional mining methods. Additionally, future research could entail expanding these tools to the broader underground mining industry, such as underground stone or coal.


Page last reviewed: September 16, 2020
Page last updated: September 16, 2020