Dual-Indicator Micro-Electro-Mechanical System Monitoring Method for Rock Instability Early Warning

Traditional displacement monitoring struggles to provide early warnings for sudden rock collapses. This study proposes a Micro-Electro-Mechanical System (MEMS) sensor-based monitoring method using dual dynamic indicators. By analyzing sensor mechanisms through vibration dynamics theory and establishing theoretical models via moment equilibrium equations, we derived a quantitative correlation between natural frequency (NF) and safety factor, identifying a 4:3 scaling coefficient specific to toppling-type unstable rocks. An innovative stability criterion algorithm integrating NF and the root mean square velocity amplitude ratio (RMS-VAR) was developed, revealing that RMS-VAR detects stability degradation three times faster than tilt measurements. Laboratory tests confirmed MEMS sensors’ reliability in monitoring NF, amplitude ratio, and tilt angles, demonstrating that sensor deployment strategies and rock geometry jointly determine model accuracy. This quantitative approach offers a novel solution for monitoring sudden geological hazards, combining timeliness with cost-effectiveness.

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Institutions

Publication Details

Journal
Applied Sciences
Published
2025-04-11
DOI
https://doi.org/10.3390/app15084210
Citations
2
Primary Topic
Rock Mechanics and Modeling
Type
article
Field-Weighted Citation Impact
1.73

Funders

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article

Dual-Indicator Micro-Electro-Mechanical System Monitoring Method for Rock Instability Early Warning

Mowen Xie, Xiaoyong Zhang, Chen Chen, Yan Du
2 citations
Applied Sciences
Rock Mechanics and Modeling
1.73
article

Dual-Indicator Micro-Electro-Mechanical System Monitoring Method for Rock Instability Early Warning

Mowen Xie, Xiaoyong Zhang, Chen Chen, Yan Du
article en
2 citations

Abstract

Traditional displacement monitoring struggles to provide early warnings for sudden rock collapses. This study proposes a Micro-Electro-Mechanical System (MEMS) sensor-based monitoring method using dual dynamic indicators. By analyzing sensor mechanisms through vibration dynamics theory and establishing theoretical models via moment equilibrium equations, we derived a quantitative correlation between natural frequency (NF) and safety factor, identifying a 4:3 scaling coefficient specific to toppling-type unstable rocks. An innovative stability criterion algorithm integrating NF and the root mean square velocity amplitude ratio (RMS-VAR) was developed, revealing that RMS-VAR detects stability degradation three times faster than tilt measurements. Laboratory tests confirmed MEMS sensors’ reliability in monitoring NF, amplitude ratio, and tilt angles, demonstrating that sensor deployment strategies and rock geometry jointly determine model accuracy. This quantitative approach offers a novel solution for monitoring sudden geological hazards, combining timeliness with cost-effectiveness.

Applied SciencesVol. 15(8)
Beijing Water Science and Technology Institute (CN), University of Science and Technology Beijing (CN)
National Natural Science Foundation of China, State Key Laboratory for GeoMechanics and Deep Underground Engineering, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 19%
Rock Mechanics and Modeling
1.73
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Dual-Indicator Micro-Electro-Mechanical System Monitoring Method for Rock Instability Early Warning — Mowen Xie, Xiaoyong Zhang, et al. · Applied Sciences (2025) | TGRS Research Map | TGRS