@article{CHEN2022, 
author = {Yang CHEN and Lizheng DENG and Lida HUANG and Tao CHEN and Jianguo CHEN and Hongyong YUAN},
title = {Landslide early warning model based on acoustic emission monitoring},
year = {2022},
journal = {Journal of Tsinghua University (Science and Technology)},
volume = {62},
number = {6},
pages = {1052-1058},
keywords = {disaster early warning model, landslide, acoustic emission, ring down count, wavelet transform},
url = {https://www.sciopen.com/article/10.16511/j.cnki.qhdxxb.2022.22.030},
doi = {10.16511/j.cnki.qhdxxb.2022.22.030},
abstract = {Landslides are common geological disasters that frequently occur in mountainous areas. Landslides can threaten the safety of people around hidden danger points; thus, timely, accurate monitoring and early warning systems are needed for landslides. This study analyzed the acoustic emission signal and displacement monitoring parameters for existing acoustic emission monitoring systems and early warning models of the deformation before a landslide. A landslide early warning model was then developed based on acoustic emission monitoring using wavelet transforms and an improved tangential angle model. The reliability was verified against laboratory simulation data from Loughborough University, UK. Monitoring equipment was then installed at a key point in the very large landslide prone area in Liannan County, Guangdong Province, China. The acoustic emission monitoring parameters and the displacement parameters were then compared with the measured deformation of the slope. The results show that the acoustic emission monitoring parameters are more sensitive and more accurate than the displacement parameters.}
}