# Dual-Indicator Micro-Electro-Mechanical System Monitoring Method for Rock Instability Early Warning
## 1 Introduction  
As a major energy-producing country, China has gained significant economic benefits from the development of cascade power stations and mining operations. Nevertheless, geohazards, including slope collapse disasters, continue to impose substantial socioeconomic impacts [1]. Due to complex geological conditions, frequent seismic activities, and engineering construction disturbances, rock mass internal stress imbalance frequently leads to collapse accidents [2]. The prevention of unstable rock mass collapse poses a major challenge in engineering geological disaster mitigation, given its sudden occurrence and spatially dispersed nature. Consequently, real-time stability monitoring and the early warning of collapsing unstable rock masses remain critical practical issues in geotechnical engineering. For rock masses or blocks exhibiting potential instability on natural slopes, the deterioration of their primary structural planes plays a decisive role in stability control. Experimental validations and practical applications have demonstrated the effectiveness of monitoring methods utilizing vibration characteristics to assess structural plane degradation. The NF of an unstable rock mass, as its intrinsic dynamic parameter, is uniquely determined by the mass matrix and stiffness matrix. [PERSON] et al. [3] employed passive seismic techniques to analyze the quantitative relationship between the NF and the stabilityof toppling rock masses. [PERSON] et al. [4] employed ambient vibration response to verify stability variations in rock mass reinforcement effectiveness. [PERSON] et al. [5] conducted a dynamic characteristic analysis of coastal slopes using ambient vibration, delineating deep structural features that were superficially undetectable. Additional studies have explored unstable rock mass vibration responses through vibration mechanics and dynamic mathematical analyses [6]. [PERSON] et al. [7] employed dynamics theory to analyze energy transitions during rock mass sliding, establishing theoretical formulas for elastic-impact velocity and acceleration. Internationally, seismic monitoring equipment has been predominantly employed for large unstable rock mass vibration studies [8]. [PERSON] et al. [9] identified directional amplification effects correlated with structural plane orientation and slope deformation through environmental vibration data analysis. [PERSON] et al. [10] utilized passive seismic measurements to map subsurface structural plane distributions (30-90 m depth). [PERSON] et al. [11, 12] performed modal analyses using 1 h environmental vibration datasets, enabling the spatial mapping of undetectable subsurface fractures via frequency-dependent vibration pattern correlations. [PERSON] et al. [3] observed linear polarization in unstable rock mass particle trajectories through spectral ratio comparisons with the parent rock. These investigations confirm that vibration-derived dynamic indicators offer innovative approaches for collapse monitoring. However, traditional seismic equipment and single-index methodologies prove inadequate for ensuring monitoring accuracy and early-warning reliability. MEMS sensing, as a miniaturized technology integrating micro-mechanical structures, sensors, actuators, and electronic circuits, provides a reliable method for monitoring data acquisition in unstable rock masses. Compared to conventional vibration sensing, MEMS technology provides distinct advantages including miniaturization, low cost, low power consumption, and wide frequency response--essential features for complex engineering scenarios. [PERSON] et al. [13] utilized MEMS sensors to conduct monitoring verification on highway slope displacement. [PERSON] et al. [14] implemented a real-time monitoring methodology for low-speed machinery using IoT technology and MEMS sensors.