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Determining Underground Mining Work Postures Using Motion Capture and Digital Human Modeling.

Timothy J Lutz¹, Joseph P DuCarme¹, Adam K Smith¹

¹Mine Safety and Health Research, National Institute for Occupational Safety and Health, Pittsburgh, USA.

Journal of Environment and Health Sciences

|June 20, 2017

Summary

Mining accidents involving continuous mining machines (CMMs) can be reduced using intelligent proximity detection (iPD). NIOSH research shows miner posture analysis helps improve CMM safety by identifying body positions.

Keywords:

Mine safety Motion capture Posture identification Proximity detection Underground coal

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Area of Science:

Occupational Safety and Health
Mining Engineering
Human Factors Engineering

Background:

Remote-controlled continuous mining machines (CMMs) are associated with an average of 65 lost-time accidents annually in U.S. mines.
The National Institute for Occupational Safety and Health (NIOSH) is developing automated, intelligent proximity detection (iPD) systems for CMMs to enhance worker safety.

Purpose of the Study:

To improve CMM proximity detection systems by enabling tracking of multiple workers' identity, position, and posture.
To enhance safety by selectively disabling machine functions based on worker proximity and posture.

Main Methods:

Motion capture data was collected from 12 human subjects performing various postures.
Joint angles of the back, hips, and knees were calculated from the motion capture data.
Analysis focused on identifying correlations between lower body postures and joint angle variations.

Main Results:

Miner posture significantly influences the magnetic field used by proximity detection systems.
Specific joint angle changes in the hips and knees correlate with distinct lower body postures.
This data can inform the development of posture-aware safety systems.

Conclusions:

Identifying miner posture through joint angle analysis is a viable method for enhancing proximity detection.
Integrating posture detection into iPD systems can improve safety around continuous mining machines.
Further research can refine these methods for real-world mining applications.