Research Status and Development Trend of Monitoring and Early Warning Technologies for Unstable Rock Masses
SUN Xianbo
DONG Kewen
PENG Pangdi
JIN Haoyu
HUANG Yong
YI Jinqiao
HU Tao
ZHU Li
SONG Jian
Abstract：To improve the monitoring and early warning levels and prevention and control efficiency of instability and collapse disasters of unstable rock masses under complex geological conditions,through extensive retrieval and in-depth analysis of relevant domestic and international literature,a systematic study was conducted on the geological disasters of unstable rock masses,as well as the current research status,existing problems,and development trends of monitoring and early warning technologies for unstable rock masses.The results indicated that rockfall monitoring and early warning technologies had evolved from traditional manual observation to real-time sensor-based monitoring using three-dimensional laser scanning and fiber optic sensing,and further integrated machine learning(ML)and deep learning(DL)for intelligent identification.Microseismic monitoring and multi-physical field coupling simulation had also become important supplements.However,current technologies still suffered from limited accuracy in identifying disaster-breeding features,the absence of dynamic criteria for instability precursors,and restricted timeliness of early warnings.Future research could focus on multi-source data fusion and the integration of mechanism-driven and data-driven modeling to establish an efficient and intelligent early warning and emergency response system,promoting a shift in rockfall disaster prevention from passive management to active control.
Keywords：unstable rock massgeological disastersmonitoring and early warning technologymachine learningdeep learning
Publication Date：2025-12-30
Online Publishing Date：2025-12-10(First online date of this platform, not the publication date of the document)
Pages：6( 580-584,600 )