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Data for evaluating mine roof stability via acoustic impact
Travis Wiens1, Shahriar Islam1
1Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, Sk, Canada.
Data in Brief
|February 11, 2022
Summary
This study introduces a new dataset of 3309 acoustic recordings from underground potash mines. These recordings, labelled by experts, will aid in developing automated systems for assessing mine roof stability.
Area of Science:
- Geotechnical Engineering
- Mining Safety
- Acoustics
Background:
- Underground mine roof stability is paramount for miner safety.
- Current roof assessment relies on subjective acoustic interpretation (tight vs. drummy).
- Objective methods are needed to enhance the reliability of roof condition assessments.
Purpose of the Study:
- To present a novel, expert-labelled dataset of acoustic recordings from underground mine roof impacts.
- To facilitate the development of machine learning models for automated roof stability assessment.
- To support research in mining geophysics and safety.
Main Methods:
- Collected 3309 acoustic recordings of roof impacts using a long bar.
- Recordings were obtained from multiple sites across 5 potash mines in Saskatchewan, Canada.
- An experienced miner labelled each recording as 'tight' (safe) or 'drummy' (unsafe).
Main Results:
- A comprehensive dataset of labelled acoustic signals is now available.
- The dataset captures variations in sound signatures associated with different roof conditions.
- Provides a foundation for computational analysis of roof acoustics.
Conclusions:
- The presented dataset is a valuable resource for advancing automated roof stability monitoring.
- This work can lead to improved safety protocols in underground mining operations.
- Further research can leverage this data to create robust diagnostic tools.
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