DYNAMIC IDENTIFICATION METHOD OF SLOPE IMPENDING LANDSLIDE MOMENT BASED ON HYPOTHETIC TESTING THEORY
WANG Dong1，CAO Lanzhu1，PIAO Chunde2，XUE Yingdong3，BAI Runcai1
(1. College of Mines，Liaoning Technical University，Fuxin，Liaoning 123000，China；
2. School of Resource and Earth Science，China University of Mining and Technology，Xuzhou，Jiangsu 221008，China；
3. Western Surface Mine，Pingzhuang Energy Corporation，Chifeng，Inner Mongolia 024076，China )
Abstract：The displacement monitoring technology is used more widely in the slope engineering. How to master the slope stability opportunely based on the dynamic monitoring information and determine the impending landslide moment is a key problem for effectively carrying out the landslide warning and avoiding the landslide disaster. On the basis of analyzing various landslide criteria，the displacement acceleration a≥0 is regarded as the impending landslide criterion. The displacement velocity variable generated by the monitored displacement records is regarded as a random variable. It is taken for granted that the displacement velocity variable follows normal distribution in the slope constant velocity deformation stage and is not normal distribution in the slope accelerating deformation stage；then a dynamic identification method of slope impending landslide moment based on Lilliefors testing is proposed. According to the monitoring data in the process of 9•15 landslide of the top slope of Pingzhuang Western Surface Mine，the distribution characteristics of the displacement velocity variables in different stages are tested；the results show that the displacement velocity variables are normal distribution in the constant deformation stage and exponential distribution in the accelerating deformation stage；at the same time，the displacement acceleration variables are normal distribution for some time before the slope sliding sharply，which shows that the rationality of the presented method. The results show that the presented method can identify the impending landslide moment opportunely and accurately，so as to improve the reliability of the landslide early warning effectively.
2012, Vol. 31 
